Rapid isolation of monoclonal antibodies from animals

ABSTRACT

Methods and compositions for identification of candicate antigen-specific variable regions as well as generation of antibodies or antigen-binding fragments that could have desired antigen specificity are provided. For example, in certain aspects methods for determining amino acid sequences of serum antibody CDR and abundancy level are described. In some aspects, methods for determining nucleic acid sequences of antibody variable region sequences and frequency are provided. Furthermore, the invention provides methods for identification and generation of antibody or antigen-binding fragments that comprise highly-represented CDR.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No. 13/109,467, filed May 17, 2011, now issued as U.S. Pat. No. 9,090,674, which claims the benefit of U.S. Provisional Patent Application Nos. 61/345,538 and 61/377,816, filed May 17, 2010 and Aug. 27, 2010, respectively, the entirety of each of which are incorporated herein by reference.

GOVERNMENT SUPPORT CLAUSE

This invention was made with government support under HR0011-10-1-0052 awarded by Defense Advanced Research Projects Agency. The government has certain rights in the invention.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates generally to the field of antibody analysis and generation, such as antibody discovery from immunized animals. More particularly, it concerns novel methods and compositions for identification and/or production of desired antibodies or antigen-binding fragments. It also concerns identification of monoclonal antibodies from any mammal and more generally any animal that has an adaptive immune response that leads to the expression of soluble immunoglobulin and for which genomic information on its immunoglobulin locus is available.

2. Description of Related Art

Over the last 12 years, the development of cancer therapeutic antibodies, such as HERCEPTIN® (Trastuzumab, anti-Her2), RITUXAN® (Rituximab, anti-CD20), Eribitux/VECTIBIX® (Cetuximab/Panitumumab, anti-EGFR), AVASTIN® (anti-VEGF) and others have saved many tens of thousands of lives world-wide. Antibody therapeutics offer distinct advantages relative to small molecule drugs, namely: (i) better understood mechanisms of action; (ii) higher specificity and fewer-off target effects; (iii) predictable safety and toxicological profiles. Currently, there are more than 200 antibody therapeutics in clinical trials in the U.S., many of them for cancer treatment.

The discovery of monoclonal antibodies is an immensely important aspect in therapeutic antibody development. Additionally, monoclonal antibodies are widely used for numerous diagnostic and analytical purposes. Since the development of the hybridoma technology by Kohler and Milstein 35 years ago (Kohler and Milstein, 1975), a variety of methods for the generation of MAbs have been developed. Such methods include B cell immortalization by genetic reprogramming via Epstein-Barr Virus (Traggiai et al., 2004) or retrovirus-mediated gene transfer (Kwakkenbos et al., 2010), cloning of V genes by single cell PCR (Wrammert et al., 2008; Meijer et al., 2008), and methods for in vitro discovery via the display and screening of recombinant antibody libraries (Clackson et al., 1991; Feldhaus et al., 2003; Harvey et al., 2004; Schaffitzel et al., 1999; Hosse et al., 2006; Mazor et al., 2007; Zahnd et al., 2007; Kretzschmar and von Ruden, 2002). Both in vitro and in vivo methods for antibody discovery are critically dependent on high-throughput screening to determine antigen specificity. Recently, B cell analysis has been expedited by microengraving techniques that utilize soft lithography for the high-throughput identification of antigen-specific B cells, however, this is at the cost of considerable technical complexity due to the need for antibody V gene amplification and cell expansion (Jin et al., 2009; Love et al., 2006).

Similarly, the success of in vitro antibody discovery techniques is dependent on screening parameters including the nature of the display platform, antigen concentration, binding avidity during enrichment, multiple rounds of screening (e.g., panning or sorting), and importantly, on the design and diversity of synthetic antibody libraries (Hoogenboom, 2005; Cobaugh et al., 2008; Persson et al., 2006).

Current use of display technologies coupled with library screening systems such as a phage display where antibodies are isolated by panning has a number of significant problems—in particular, some antibodies produced by a library may cause the death of the organism expressing them and therefore they simply cannot be detected. There is a particular problem when one is searching for antibodies specific to an antigen from a pathogen which might be homologous to one produced by the host expression system (e.g., E. coli) then important antibodies cannot be expressed. The use of E. coli to express libraries of human antibodies also suffers from the problem of codon usage—codons used by humans for specific amino acids can frequently not be the optimum ones for the same amino acid in E. coli or other host systems. This means that an important antibody might not be expressed (or at least not in sufficient quantities) since the codons in its sequence are highly inefficient in E. Coli, resulting in the E. coli being unable to read through and express it in full. Codon optimization of antibody libraries is obviously not an option since the libraries would first have to be sequenced, which defeats the main advantages of using libraries.

There is a pressing need to identify biologically relevant antibodies that exhibit a beneficial effect in controlling diseases. Mammals mount antibody (humoral) immune responses against infectious agents, toxins or cancer cells. Diseased individuals produce circulating antibodies that recognize the disease agent and in many cases (e.g., in patients that recover from an infection or in cancer patients in remission); these antibodies play a key role in recovery and therapy. Currently there are no methods available to identify the circulating antibodies in blood and to produce the antibodies that are specific to the disease agent and have a therapeutic effect.

On the other hand, the isolation of monoclonal antibodies from different animal species is of great value for the development of therapeutics and diagnostics. A major limitation of the existing methods for isolation of monoclonal antibodies is that their application is limited to a very small number of species. Different animals have evolved distinct ways of diversifying their antibody repertoire and thus can produce antibodies that recognize distinct epitopes on an antigen or display very high affinity for a particular antigen, compared to mice and humans. For example, it is well known in the art that antibodies from rabbits generally display much higher affinity than those produced from mice.

Current production of monoclonal antibodies from a particular species using the hybridoma technology necessitates that B cell are immortalized by fusion to a myeloma from that species. Such myeloma cell lines are difficult and time consuming to develop and therefore exist only for mice, primates, rabbits and sheep. Alternatively, researchers have attempted to generate interspecies hybridomas, by fusing a mouse myeloma cell line with B cells from an animal for which autologous myeloma cell lines are not available. However, interspecies hybrids are generated with very low efficiency and are unstable, ceasing to produce monoclonal antibodies after a few passages. Thus at present the production of monoclonal antibodies from the vast majority of animals that have an adaptive immunoglobulin system is a major challenge. Moreover, even for species for which stable B cell fusions can be generated (rabbits, mice, sheep and primates) the isolation of monoclonal antibodies using the hybridoma technology is a lengthy process requiring 2-6 months after animal sacrifice.

Alternatively monoclonal antibodies can be isolated in vitro from large libraries of the variable (V) chains of the immunoglobulin repertoire from an immunized animal and then screening such libraries by a variety of display methods such as phage display, yeast display or bacterial display. Once again the utility of these methods is limited to the few species for which extensive information on their immunoglobulin repertoire is available, namely mice, primates and rabbits. This is because, the cloning of the immunoglobulin repertoire requires the availability of sets of oligonucleotide primers capable of amplifying the majority, preferably all, of the immunoglobulin variable regions that are generated in that animal via somatic recombination mechanisms. This in turn requires extensive information on the sequences of immunoglobulins expressed in a particular species and it is not available for the vast majority of animals that have an antibody-encoding, humoral immunity system. Additionally it is not known whether the antibodies isolated by combinatorial library screening correspond to those that have been expanded by the immune system and produced in large amounts in animals.

Obviously all of these techniques are somewhat complex, inconvenient, and time consuming. Therefore, there remains a need to develop a more efficient and accurate method for identifying antigen-specific antibodies or monoclonal antibodies directly from a patient or any animal.

SUMMARY OF THE INVENTION

Aspects of the present invention overcome a major deficiency in the art by providing novel methods for determining serum antibody sequences or identifying abundant antibody sequences from serum, B cells, or directly from lymphoid tissues or from isolated B cells. Accordingly, in a first embodiment there is provided a method for identifying abundant antibody sequences in circulation, comprising: a) determining amino acid sequences of at least the complementarity determining region 3 (CDR3) of the VH and VL regions of antibodies in a serum-containing sample of a subject, to provide serum antibody sequences; and b) identifying the antibody sequences that exhibit a threshold level of abundancy relative to other serum antibody sequences. A “serum-containing sample” is intended to include any blood-related sample, such as a serum-containing sample, a plasma sample, or a blood sample with an additive. In certain aspects, the amino acid sequences so determined comprises sequences of whole VH and VL regions.

In a second embodiment, there may be provided a method for generating one or more antibodies or antigen-binding fragments, comprising: a) obtaining sequence and abundancy information of antibody amino acid sequences of at least the CDR3 of VH and VL regions of antibodies present in the serum of a subject; b) identifying those sequences that exhibit at least a threshold level of abundancy; and c) generating one or more antibodies or antigen-binding fragments that comprise one or more of the abundant amino acid sequences so determined. For example, generation of such antibodies or antigen-binding fragments may comprise expression in a heterologous system or the use of in vitro protein synthesis.

In a further embodiment, there may be provided a method for determining antibody sequences in circulation, comprising: a) obtaining nucleic acid sequences, and the corresponding amino acid, sequence information of one or more VH and VL genes in mature B cells of a subject and the corresponding amino acid sequences; b) obtaining mass spectra of peptides derived from serum antibodies of the subject; and c) using the sequence information and the mass spectra to determine the amino acid sequence of VH and VL regions of one or more antibodies in circulation.

In an additional embodiment, there may be provided a method for generating antibodies, comprising: a) obtaining sequence and abundancy information of amino acid sequences of VH and VL regions of antibodies in a serum-containing sample of a subject; and b) generating one or more antibodies that comprise VH and VL regions of the serum antibodies based on the sequence and abundancy information.

In a certain embodiment, there may also be provided a method for preparing CDR3-containing peptide fragments from serum antibodies of a subject, comprising: a) obtaining nucleic acid, and corresponding amino acid, sequence information of at least the CDR3 of VH and VL genes in mature B cells of a subject; b) using the sequence information to select a protease; and c) preparing CDR3-containing peptide fragments from serum antibodies of the subject with the protease. Such a protease may predominantly do not cleave CDR3 of the VH and VL peptides. For example, the protease may cleave at sites adjacent to the CDR3 regions, leaving the CDR3 regions substantially intact.

In other aspects, there may also be provided methods related to nucleic acid information in B cells. For example, there may be provided a method for generating one or more antibodies or antigen-binding fragments, comprising: a) obtaining sequence and abundancy information of nucleic acid sequences of at least the CDR3 of VH and VL genes in a plasma cell population of a subject; and b) identifying those sequences that exhibit at least a threshold level of abundancy; and c) generating one or more antibodies or antigen-binding fragments comprising one or more of the amino acid sequences corresponding to identified nucleic acid sequences.

The inventors found that abundant antibody sequences present in the serum may be correlated with abundant antibody genes in B cells, especially B cells from a selected organ, such as bone marrow. In a further embodiment, there may be provided a method for identifying abundant antibody sequences in circulation, comprising: a) determining sequence and abundancy information of nucleic acid sequences of at least the CDR3 of the VH and VL genes in plasma cells of a subject; and b) identifying those antibody amino acid sequences that correspond to antibody nucleic acid sequences that exhibit at least a threshold level of abundancy, thereby identifying abundant antibody sequences in circulation. For example, the identified antibody amino acid sequences may be sequences of a selected class of antibodies, such as IgG, IgM, or IgA.

In certain aspects, determining or obtaining abundance information for vV gene sequences (e.g., a VH, VL) comprises obtaining the abundance information for a cluster of high homologous sequences derived from the same VDJ lineage. For example, multiple sequences can be aligned to identify clusters of highly homologous sequences (e.g., sequence that differ by the results of somatic hypermutation) and then the clusters can be ranked to determine the prevalence of the clusters. Accordingly, in aspects wherein VH and VL domains are paired to form a complete antibody V domain VH and VL domains belonging to similarly ranked clusters can be paired.

In further embodiments, there may be provided methods for monoclonal antibody generation in any animal are provided. The methods may overcome prior limitations by capitalizing on high throughput DNA sequencing of immunoglobulin DNA from a subject such as an immunized animal followed by bioinformatic analysis of the antibody nucleic acid sequence repertoire for the identification of monoclonal antibodies with specificity to the immunization antigen. The antibodies thus identified may be class-switched and somatic hypermutated or may be of a selected antibody class, such as IgG or IgA in humans and mice or their equivalents in other animals.

In certain embodiments, there may be provided a method for identifying candidate antigen-specific antibody variable region nucleic acid sequences. The method may comprise obtaining a pool of antibody variable region nucleic acids from a population of nucleic acids of a lymphoid tissue of a subject, preferably without separation of B cells from the lymphoid tissue. The subject may have been exposed to an antigen, such as an infectious agent, an immunization agent, or a toxin. The variable region may at least contain a CDR3 region or a full length region containing CDR1-3, and may be a variable heavy chain or a variable light chain or both.

The method may comprise immunizing the subject. The method may further comprise isolation of a lymphoid tissue. The lymphoid tissue isolation may at least or about 1, 2, 3, 4, 5, 6, 6, 8, 9, 10 days or any intermediate ranges after immunization. The method may further comprising obtaining a population of nucleic acids of lymphoid tissue, preferably without separation B cells from the lymphoid tissue. The lymphoid tissue may be a primary, secondary or tertiary lymphoid tissue, such as bone marrow, spleen, or lymph nodes. The subject may be any animal, such as mammal, fish, amphibian, or bird. The mammal may be human, mouse, primate, rabbit, sheep, or pig.

The nucleic acid pool of antibody variable regions may be a cDNA pool. Obtaining the nucleic acid pool may comprise the use of reverse transcriptase. The method for obtaining the nucleic acid pool, for example, may comprise rapid cDNA end amplification (RACE), PCR amplification, or nucleic acid hybridization. Without separation of B cells from the lymphoid tissue, the nucleic acid population of the lymphoid tissue may contain other non-B cell nucleic acids as well as non-antibody nucleic acids. For the antibody sequence separation, antibody-specific primer or probes may be used, such as primer or probes based on known antibody constant region cDNA sequences. In alternative aspects, the nucleic acid pool may be a genomic nucleic acid pool.

The method may further comprise determining sequences and occurrence frequency of antibody variable region nucleic acids in the pool. In a further embodiment, the method may comprise identifying abundant variable region sequences. In specific embodiments, the method may further comprise identifying CDR3 sequences of the antibody variable region nucleic acid sequences, such as by homolog searching. Since CDR3 is the most variable region, variable region sequence frequency is preferably based on corresponding CDR3 frequency. Particularly, the occurrence frequency of a selected variable region sequence may be further defined as the sum of the occurrence frequency of any variable region sequences having the same or similar CDR3 sequences as that of the selected variable region sequence. The similar CDR3 sequences may be at least about 90, 91, 92, 93, 94, 95, 96, 97, 98, 99% or any intermediate ranges. For example, variable region sequences may be grouped based on the same or similar CDR3 sequences and each group has the same frequency as defined by the sum of the frequency of all the sequences in the same group. In other aspects, the frequency of variable region sequences may be the frequency of each different variable region sequence or based on similarity of full length variable regions, which contains CDR1, CDR2, and CDR3.

In certain aspects, identification of abundant CDR3 sequences may be performed followed by identification of full length variable regions containing the identified abundant CDR3 sequences. For example, primer or probes may be generated based on the abundant CDR3 sequences and used to enrich or amplify antibody variable region sequences encoding the abundant CDR3 sequences.

In exemplary aspects, such abundant sequences may occur in total at a frequency of at least 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10% or any intermediate ranges in the sequences so determined. The abundant variable region sequences so identified may be candidate antigen-specific sequences.

For generation of antigen-specific antibody or antibody fragments, the method may further comprise selecting a pair comprising nucleic acid sequences of a V_(H) and a V_(L) at similar abundancy levels or a pair comprising nucleic acid sequences that belong to a cluster of nucleic acid sequences comprising similar abundancy. For example, the V_(H) nucleic acid sequence in the pair is the most abundant V_(H) sequence and the V_(L) nucleic acid sequence in the pair is the most abundant V_(L) sequence. Alternatively, the V_(H) and a V_(L) at similar abundancy levels may be any V_(H) and a V_(L) have the same relative rank order in the V_(H) or V_(L) subpopulation, respectively, or similar concentration levels. For example, the third most abundant V_(H) may be paired with the third most abundant V_(L). In still further aspects, a V_(H) and/or V_(L) may be aligned with other identified V_(H) or V_(L) sequences to identify clusters of highly homologous sequences (e.g., sequences differing by the results of hypermutation) the clusters are then ranked and the V_(H) can be paired with a V_(L) which belongs to a cluster of similar rank.

The method may further comprise generating antibody or antibody fragments comprising amino acid sequences encoded by the paired nucleic acid sequences of V_(H) and V_(L), At least one of the generated antibody or antibody fragments may bind the antigen that the subject has been exposed to, such as the immunization agent used to immunize the subject. For example, the abundant variable region sequences may be directly chemical synthesized, such as an automatic synthesis method. The method may further comprise expressing the abundant variable region sequences (e.g., synthesized) in an in vitro expression system or a heterologous cell expression system.

The subject may be any animal, preferably a mammal or a human. The subject may have a disease or a condition including a tumor, an infectious disease, or an autoimmune disease, or have been immunized. In certain aspects, the subject may recover or survive from a disease or a condition such as a tumor, an infectious disease, or an autoimmune disease. In further aspects, the subject may be under or after prevention and treatment for a disease or a condition, such as cancer therapy or infection disease therapy, or vaccination. For example, the subject has or has been exposed to an antigen which is an infectious agent, a tumor antigen, a tumor cell, an allergen or a self-antigen. Such an infectious agent may be any pathogenic viruses, pathogenic bacteria, fungi, protozoa, multicellular parasites, and aberrant proteins such as prions, as wells as nucleic acids or antigens derived therefrom. An allergen could be any nonparasitic antigen capable of stimulating a type-I hypersensitivity reaction in individuals, such as many common environmental antigens.

Tumor antigen could be any substance produced in tumor cells that triggers an immune response in the host. Any protein produced in a tumor cell that has an abnormal structure due to mutation can act as a tumor antigen. Such abnormal proteins are produced due to mutation of the concerned gene. Mutation of protooncogenes and tumor suppressors which lead to abnormal protein production are the cause of the tumor and thus such abnormal proteins are called tumor-specific antigens. Examples of tumor-specific antigens include the abnormal products of ras and p53 genes.

In certain aspects, there may be provided methods comprising obtaining sequence information of nucleic acid sequences of at least the CDR3-coding sequence of VH and VL genes in B cells of the subject. For example, the nucleic acid sequences so determined may comprise VH and VL genes. The B cells may be preferably mature B cells. For example, the mature B cells may comprise memory B cells, plasma cells, or a combination thereof. The plasma cells may comprise bone marrow plasma cells, lymph node plasma cells or spleen plasma cells. In a particular example, bone marrow plasma cells may be used. The plasma cells may be selected or enriched based on differential expression of cell markers, particularly cell surface markers, such as Blimp-1, CD138, CXCR4, and/or CD45.

Obtaining the nucleic acid sequence information may comprise determining the nucleic acid sequences and optionally the corresponding amino acid sequences in the B cells or in lymphoid tissues, or in other aspects, obtaining such information from a service provider or a data storage device. In further aspects, such nucleic acid sequence information may be used for determining the amino acid sequences of the serum antibodies.

For determining the nucleic acid sequences in the B cells or in lymphoid tissues, any nucleic acid sequencing methods known in the art may be used, including high throughput DNA sequencing. Non-limiting examples of high-throughput sequencing methods comprise sequencing-by-synthesis (e.g., 454 sequencing), sequencing-by-ligation, sequencing-by-hybridization, single molecule DNA sequencing, multiplex polony sequencing, nanopore sequencing, or a combination thereof.

In certain aspects, there may be provided methods for obtaining sequence information of amino acid sequences of at least the CDR3 of the VH and VL regions of antibodies in a serum-containing sample of a subject. Obtaining sequence information may comprise determining amino acid or nucleic acid sequences or obtaining such information from a service provider or a data storage device.

Such amino acid sequence determination methods may comprise obtaining mass spectra of peptides derived from serum antibodies of the subject. To separate peptides derived from serum antibodies, any chromatography methods may be used, such as high performance liquid chromatography (HPLC).

For determining amino acid sequences, there may be provided methods comprising isolating or enriching a selected class of serum antibodies such as IgG, IgM, IgA, IgE, or other major Ig classes, isolating or enriching serum antibodies that bind to a predetermined antigen, and/or isolating or enriching CDR3-containing fragments of serum antibodies.

In further aspects, the methods may comprise preparing CDR3-containing peptide fragments from serum antibodies using a protease that is identified based on the sequence information of nucleic acid sequences and corresponding amino acid sequences of at least the CDR3 of VH and VL regions in mature B cells of the subject. For example, the protease cleaves VH and VL peptides at the site outside or adjacent to CDR3, thus leaving CDR3 regions substantially intact.

In certain aspects, there may also be provided method comprising enriching or purifying CDR3-containing peptide fragments. For example, such methods may comprise conjugating CDR3-containing peptide fragments with a labeled thiol-specific conjugating agent for specific conjugation of the unique cysteine at the end of the CDR3 sequences. Methods of enriching or purifying conjugated CDR3-containing peptide fragments may be based on the label on the conjugated CDR3-containing peptide fragments. Examples of the label include biotin.

Certain aspects of the invention is based, in part, on the discovery that highly abundant antibody cDNAs in plasma cells or in a lymphoid tissue are correlated with antibody specificity toward an antigen related to a disease or a condition in the subject, such as a tumor. In additional aspects, there may be provided methods comprising determining the abundancy level of the amino acid sequences of the serum antibodies or of the nucleic acid sequences of VH and VL genes in the B cells or in a lymphoid tissue, for example, by an automated method. For the determination of abundancy level of the amino acid sequences of serum antibodies, a quantitative method for mass spectrometry may be used.

In certain methods, there may be provided methods comprising identifying antibody amino acid sequences that exhibit at least a threshold level of abundancy. For example, the threshold level of abundancy is a concentration of about, at least, or at most 5, 10, 20, 30, 40, 50, 100, 200, 300, 400, 500 μg/ml (or any range derivable therein) or a level of any one of the about 20, 30, 40, 50, 60, 70, 80, 90, 100, 200 (or any numerical range derivable therein) most abundant CDR3-containing amino acid sequences of the serum antibodies.

In certain methods, there may be provided methods comprising identifying antibody nucleic acid sequences that exhibit at least a threshold level of abundancy. Such threshold level of abundancy may be at least 0.5, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15% of frequency in an antibody gene pool of the subject, for example, antibody genes in a B cell population or a lymphoid tissue. Such a B cell population may be a specific mature B cell population, such as a population of mature B cells from a selected lymphoid tissue like bone marrow, spleen or lymph nodes.

In certain further aspects, there may be provided methods comprising reporting any of the determination or identification described above. For example, such report may be in a computer-accessible format.

In certain aspects, there may also be provided methods comprising generating one or more antibodies or antigen-binding fragments comprising one or more of the abundant amino acid sequences as described above. Generation of antibodies or antigen-binding fragments may comprise chemical synthesis of V_(H) and V_(L) coding regions corresponding to abundant VH and VL amino acid sequences of serum antibodies that exhibit at least a threshold level of abundancy, or comprise, in other aspects, chemical synthesis of abundant nucleic acid sequences of VH and VL genes in B cells or in a lymphoid tissue.

The B cells may be mature B cells, particularly, plasma cells, more particularly, bone marrow plasma B cells. The generation methods may further comprise incorporating the abundant sequences into one or more expression vectors. Further aspects may comprise expressing the abundant sequences such as synthesized VH and VL sequences in any host cells, such as bacteria cells, yeast cells, insect cells, or mammalian cells.

For example, the antibodies or antigen-binding fragments so generated may bind an antigen the subject has or has been exposed to. The antigen may be an infectious agent, a tumor antigen, a tumor cell or a self-antigen. Such binding may have a monovalent affinity of at least or about 100, 200, 10³, 10⁴, 10⁵ pM, or 1, 2, 3, 4, 5 μM or any range derivable therein.

There may be further provided methods comprising evaluating the generated antibody or antigen-binding fragments for binding affinity or specificity to a predetermined antigen such as an infectious agent, a tumor antigen, a tumor cell or a self-antigen.

In a preferable aspect, each of the antibodies or antigen-binding fragments so generated comprises similarly abundant amino acid or nucleic acid sequences of V_(H) and V_(L). For example, a V_(H) sequence may have a level of abundancy ranked as the 3^(rd) most abundant VH sequence in a serum-containing sample, which may be paired with a V_(L) sequence that have a similar rank level of abundancy (for example, 3^(rd), 4^(th), or 5^(th)) in the same sample. The inventors determined that pairing V_(H) genes with V_(L) genes having a rank-order abundancy within +/−3 (e.g., the 3^(th) most abundant V_(H) with any of the 1^(st)-6^(th) most abundant V_(L)) results in antigen specific antibodies at a frequency greater than 50%.

Embodiments discussed in the context of methods and/or compositions of the invention may be employed with respect to any other method or composition described herein. Thus, an embodiment pertaining to one method or composition may be applied to other methods and compositions of the invention as well.

As used herein the terms “encode” or “encoding” with reference to a nucleic acid are used to make the invention readily understandable by the skilled artisan; however, these terms may be used interchangeably with “comprise” or “comprising” respectively.

As used herein the specification, “a” or “an” may mean one or more. As used herein in the claim(s), when used in conjunction with the word “comprising”, the words “a” or “an” may mean one or more than one.

The use of the term “or” in the claims is used to mean “and/or” unless explicitly indicated to refer to alternatives only or the alternatives are mutually exclusive, although the disclosure supports a definition that refers to only alternatives and “and/or.” As used herein “another” may mean at least a second or more.

Throughout this application, the term “about” is used to indicate that a value includes the inherent variation of error for the device, the method being employed to determine the value, or the variation that exists among the study subjects.

Other objects, features and advantages of the present invention will become apparent from the following detailed description. It should be understood, however, that the detailed description and the specific examples, while indicating preferred embodiments of the invention, are given by way of illustration only, since various changes and modifications within the spirit and scope of the invention will become apparent to those skilled in the art from this detailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

The following drawings form part of the present specification and are included to further demonstrate certain aspects of the present invention. The invention may be better understood by reference to one or more of these drawings in combination with the detailed description of specific embodiments presented herein.

FIG. 1: Flow diagram of an exemplary embodiment of the experimental methodology for the quantitative analysis of serum Ig.

FIG. 2: Schematic for isolation of monoclonal antibodies without screening by mining the antibody variable (V) gene repertoires of bone marrow plasma cells. Following immunization, mice are sacrificed and CD45R⁻CD138⁺ plasma cells are isolated. Following mRNA isolation and first-strand cDNA synthesis, variable light (V_(L)) and variable heavy (V_(H)) gene DNA is generated. High-throughput 454 DNA sequencing and bioinformatic analysis is performed to determine the V_(L) and V_(H) repertoire. The most abundant V_(L) and V_(H) genes are identified and pairing is determined by a simple relative frequency rule. The respective antibody genes are synthesized using automated robotically assisted gene synthesis. Finally, antigen-specific antibody single chain variable fragments or full-length IgGs are expressed in bacteria or mammalian cells, respectively

FIG. 3: Isolation of plasma cells from bone marrow. Left Panel: Flow cytometry plot of the total mouse bone marrow cell population labeled with anti-CD45R-APC and anti-CD138-PE antibodies. Middle panel: Bone marrow cells remaining following depletion of CD45R⁺ cells. Right Panel. Cell population isolated following magnetic sorting with anti-CD138⁺ conjugated magnetic beads.

FIG. 4: Variable light (V_(L)) and variable heavy (V_(H)) chain genes from bone marrow plasma cells. Agarose gel electrophoresis of V_(L) and V_(H) genes amplified by PCR from cDNA derived from bone marrow plasma cells of mice immunized with different antigens. From left: 1^(st) lane is DNA Ladder; 2^(nd), 4^(th), 6^(th), 8^(th) lanes are VL (˜370 bp); 3^(rd), 5^(th), 7^(th), 9^(th) lanes are VH (˜400 bp).

FIG. 5: Flow chart of an exemplary embodiment of the bioinformatics pipeline for V gene analysis. First, CDR3s were identified by homology to conserved flanking amino acid sequences motifs. CDR3s found at the highest frequency (typically with frequency >1%) were used to group the V gene sequences of interest. Homology analysis of V genes containing highly represented CDR3s was performed by multiple sequence alignment and calculation of pairwise identity. Finally, germline analysis of highly represented full-length V genes was performed to determine somatic mutations and V(D)J and V-J gene usage.

FIG. 6: Example of graphical user interface (GUI) for V gene repertoire analysis. A GUI application was developed for organization and graphical representation of high-throughput sequencing results of V genes. The program imports and organizes data sets from different samples, identifies CDRH3 and CDRL3 using the described CDR flanking motifs, and extracts CDR3 frequency distributions (SEQ ID NOS: 718-737 PRT and SEQ ID NOS: 738-747 DNA).

FIG. 7: V_(H) germline family representation in adjuvant and C1s immunized repertoires. Bar graph represents the frequency of V_(H) gene families among the top 30 V_(H) sequences in each repertoire (representing 24-47% of the total V_(H) repertoire). A clear skewing towards IGHV1 is demonstrated in immunized mice.

FIGS. 8A-8C: Homology analysis of full-length V genes containing the same CDR3. (8A) The dataset of full-length C1s-1.1 V_(H) genes (CDRH3=GNYYYAMDY (SEQ ID NO:145)) is dominated by a single sequence (65%), as all the other sequences occur at a frequency <0.8%. (8B) Frequency distribution of full-length C1s-2.2 V_(H) genes (CDRH3=WLLLAY (SEQ ID NO:21) shows multiple sequences with high frequency. (8C) Top three full-length V_(H) sequences containing C1s-2.2 CDR3 and their respective frequencies (%) (SEQ ID NOS:758-760).

FIG. 9: Comparison of high frequency CDRH3s reveals unique V_(H) genes in each mouse. Heat map showing the distribution of highly represented CDRH3s in mice injected with Adjuvant (Adv), ovalbumin (OVA), C1s, and Bright (BR). The Y-axis represents the 10 highest frequency CDRH3 sequences identified in each mouse. The X-axis compares the frequency of these prevalent CDRH3 sequences across all other mice. White: sequences found at frequencies that are not statistically significant (0.00-0.03%). Black: sequences found at a frequency of >10%.

FIGS. 10A-10B: Principal component analysis (PCA) of CDRH3 sequences from bone marrow plasma cell repertoires of different mouse groups. Ovalbumin (OVA) and Adjuvant only mice were one immunization group (derived from the same cage and same litter) while C1s and Bright mice were another immunization group. First principal component analysis identified two main cluster groups, blue and red, which represent different experiments (i.e. immunizations carried out on different dates).

FIG. 11: Percentage of CDRH3s distributed across subsets of four mouse populations. The percentage of common CDRH3 sequences between all combinations of four mice chosen from a set of eight. The percent similarity between mice immunized on the same day with either ovalbumin (OVA) or adjuvant is shown in red; percent similarity between mice immunized on the same day with either Bright or C1s is shown in blue; gray represents the similarity for every other possible combination.

FIG. 12: Construction of synthetic antibody genes. Highly represented V_(H) and V_(L) genes from bone marrow plasma cell repertoires were synthesized as single chain variable fragments (scFvs) by joining V genes with a poly-gly-ser linker. Alignment. The poly-gly-ser linker serves as the anchor point for aligning the set of desired genes. Appropriate restriction sites are added to facilitate cloning and the sequences are padded to uniform length to enable a single overlapping oligonucleotide assembly scheme for building all genes. Primary assembly. Primary fragments are generated from overlapping sets of oligonucleotides using inside-out nucleation PCR (scheme right). Secondary assembly. The second step of the assembly is a conventional overlap-extension PCR joining the primary fragments together to form the final product (scheme right). The primary PCR products are diluted with water by the liquid-handling robot and a portion of each diluted primary reaction is added to the secondary reaction (example left). Gel image. Agarose gel of typical scFv assembly products. First lane: DNA ladder; second and third lanes; primary products at ˜400 bp; fourth lane: final product at ˜810 bp.

FIGS. 13A-13B. Kinetic binding analysis of purified anti-C1s IgGs by Surface Plasmon Resonance (Biacore). (FIG. 13A) Anti-C1s 2.1L-2.1HB was injected onto a chip with immobilized C1s at 25 nM, 50 nM, 100 nM or 200 nM and (FIG. 13B) As above for anti-C1s 2.3L-2.2H injected at 2.625 nM, 5.25 nM, 10.5 nM or 21 nM.

FIG. 14: Detection of C1s by sandwich ELISA using antibodies derived by mining bone marrow plasma cell repertoires. Anti-C1s scFv 2.1L-2.1HB was coated on the plate and used as the capture antibody and anti-C1s IgG 2.3L-2.2H was used as a detection antibody.

FIG. 15. Immunoprecipitation of C1s from human serum by using antibodies derived by mining bone marrow plasma cell repertoires. Anti-C1s IgG 2.3L-2.2H was used to capture C1s in human serum, following binding on Protein-A agarose beads. Western blot analysis was performed with anti-C1s scFv 2.1L-2.1HB as the primary antibody following by detection with anti-polyHis-HRP. Lane 1: 100 kDa and 70 kDa M.W. markers; lane 2: no capture antibody; lanes 3 and 4: capture with 1.5 μg/ml and 3 μg/ml 2.3L-2.2H antibody, respectively.

FIG. 16. Sequence alignment displays the 5′ regions of all known sheep germline VH genes (IGHV). 5′ degenerate primer mixes can be designed based on these sequences and used for PCR amplification from sheep first-strand cDNA (SEQ ID NOS:779-789). (Frame 1 sequences correspond to SEQ ID NOS:790-800; Sequence Logo=SEQ ID NO:801)

FIG. 17: Amino acid sequences of chicken germline IGHV region genes (SEQ ID NOS:761-778).

DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS I. Introduction

It is remarkable to ponder how biological research has failed to address certain key issues that lie at the heart of understanding living systems. One such issue is the analysis of the composition of the polyclonal immune response in mammals. Serum antibodies play an indispensable role in protecting jawed vertebrates against challenges from environmental agents, pathogens and aberrant self cells. Yet despite immense progress in understanding the origin of immune responses and B cell development, it has not been possible to resolve at a molecular level, the ultimate outcome of humoral immunity which is to populate the serum with a protective polyclonal antibody population. For technical reasons, serum antibody responses have only been characterized with respect to titers for specific antigens with little or no information on the relative amounts and affinities and specificities of the immunoglobulins that bind to the antigen. The ability of certain aspects of the present invention to deconvolute the serum immune response by characterizing the relative abundancy and amino acid sequences of its antibody components and then to individually evaluate them for therapeutic function can revolutionize protein therapeutics.

B-cell maturation and homing are hallmarks of adaptive immunity and the production of protective immunoglobulin responses. Extensive studies in molecular immunology and genetics have led to a great appreciation of the temporal stages of B cell differentiation and many of the functions of various B cell subpopulations in mammals. The terminal—and irreversible—stage of B cell development is the formation of plasma cells that populate the bone marrow, spleen and other lymphoid tissues and serve as immunoglobulin (Ig) production factories. Fully differentiated plasma cells together with immature plasma cells (plasmablasts) that secrete lower amounts of antibody, collectively represent less than 1% of the lymphoid cells and yet are responsible for all the antibodies in circulation. From a functional standpoint, circulating antibodies are comprised of three pools: a low affinity, nonspecific pool (produced primarily by ASC of B1 and marginal zone B cell origin), a more abundant pool of polyclonal and progressively higher affinity/specificity antibodies generated in response to challenge, and a third pool of high affinity antibodies with diverse specificities towards antigens from earlier exposure. Antibodies comprising the third pool are produced throughout most of the organism's life time (as long as 50 yrs in man) without an apparent need for antigen re-stimulation. These long lasting responses play an important protective role to-reinfection and constitute the “humoral memory.” The non-specific antibody pool constitutes the “natural antibody” or “innate” component of the humoral immune response that confers early protection against pathogens. The second population of antibodies comprise the adaptive immune response and declines rapidly in intensity within weeks after challenge (Rajewsky, 1996; Manz et al., 2005; Shapiro-Shelef and Calame, 2005; Lanzavecchia and Sallusto, 2009).

Plasma cells represent less than 1% of the lymphoid cells and yet they are responsible for all the antibodies in circulation (Rajewsky, 1996; Manz et al., 2005; Shapiro-Shelef and Calame, 2005; Lanzavecchia and Sallusto, 2009). In mice and humans, antibodies are present in serum at concentrations between 10-20 mg/ml, of which 85% is IgG, about 7% is IgM and another 7-10% monomeric IgA (Manz et al., 2005). Analysis of the antibody secreting cell (ASC) populations in the mouse indicates that serum may contain as many as 500 different antibodies of which multiple may be of the same antigen specificity. However, low abundancy antibodies present at concentrations <20 μg/ml (about 1 nM) are not likely to play a significant role, at least individually, in cancer surveillance and killing.

Remarkably, given the immense importance of serum antibodies in mammalian immunity, there is still no way to quantitatively characterize the relative concentrations and determine the sequence and affinity/specificity of the various antibodies that comprise the serum Ig pool. For technical reasons, serum antibody responses have only been characterized with respect to titers for specific antigens. Proteomic analysis of serum Igs has not been possible, first because the junctionally diverse and somatically mutated amino acid sequences of fully assembled V regions in Igs are essential for the interpretation of MS spectra but are not known a priori. In other words MS analysis of serum IgG requires knowledge of the amino acid sequences of the proteins but these sequences are not known. Second, because serum is a highly complex mixture of numerous proteins shot gun proteomic methods are extremely difficult to implement. Third, proteomic methods cannot inform on antibody specificities and biological function.

Immunologists have relied on the isolation of antibodies with desired specificity by immortalization using techniques such as the hybridoma technology or B-cell immortalization by viral (EBV) infection or alternatively, by B-cell screening and cloning. However, these approaches cannot capture the repertoire of antibodies in circulation. Plasma cells which produce antibodies cannot proliferate and cannot be fused or immortalized. It is not possible to know whether an antibody isolated from immortalizing/cloning memory B-cells is represented in the serum and at what level relative to other antibodies. For these reasons the art does not contain any information on how to isolate the antibodies that are present in circulation, especially those antibodies that are present in higher abundancy or are specific for binding to a disease causing antigen.

In addition, these approaches cannot be generally applied to any animal other than a small set of mammals, mice, primates and in some cases rabbits for which suitable tools for B cell immortalization have been developed. Moreover, these methods are very time consuming and as a result it can take many months between the sacrifice of an animal and the isolation of an antigen specific antibody.

This invention seeks to overcome the prior art disadvantages and develops methods for the quantitative molecular deconvolution of antibody responses in humans and animals. For example, high-throughput sequencing, proteomic and/or bioinformatic analyses could be combined to identify the sequence and relative abundancy of highly represented immunoglobulins (Igs) in circulation or in lymphoid tissues. In certain further embodiments, the genes for the variable domains of these antibodies could then be synthesized, the respective IgGs or antibody fragments such as scFvs expressed and purified and then the antibodies or antibody fragments could be analyzed for binding to an antigen in the source of the subject, such as infectious agents or cancer cells of interest.

For quantitative molecular deconvolution of antibody response from serum, there may be provided a method with exemplary embodiments illustrated in FIG. 1. In certain embodiments one or more of the steps may be optional and variations of the steps may be used to carry out the same purpose. First, high-throughput sequencing like NextGen sequencing of V gene cDNAs from mature B-cells (memory and plasmablasts) in peripheral blood, or from plasma cells in the bone marrow and spleen (when available) is used to create a database of the amino acid sequences of the patient's antibodies. In certain aspects, DNA sequencing could be used to build a sequence database of all the antibodies that are made by an individual. Second, for proteomic analysis the immunoglobulin fraction from patient's serum is isolated, and antibodies are fractionated by various affinity methods for Ig class separation, and also by affinity binding on various antigens of interest. Third, the Ig polypeptides in the various fractions are fragmented using proteases that preserve the integrity of the CDR3 regions. The CDR3 regions are unique or near unique identifiers of the different antibodies. The CDR3 peptides are also enriched from unrelated peptide by virtue of methods that capitalize on the presence of a Cys residue in the peptide. For example, reagents that react with thiols to introduce a biotin are used. Fourth, the CDR3 peptides are then resolved and sequenced by shotgun proteomics LC-MS/MS methods that provide absolute quantitation of the various CDR3 sequences in the pool. Fifth, the MS data is interpreted with reference to the amino acid sequence database generated in the first step above. Sixth, the most abundant V_(H) and V_(L) genes identified in the serum are synthesized by total gene synthesis. Seventh, V_(H) and V_(L) genes of the same abundancy are paired into IgG which is expressed and characterized for antigen binding affinity.

In further embodiments antigen specific antibodies are isolated by affinity chromatography with immobilized antigen. Then, peptides that are unique or otherwise can identify sequences encoded by V gene families are identified as in the paragraph above. Subsequently VH and VL genes corresponding to peptides having the same abundance (frequency) or rank-order abundance are synthesized and paired into IgG which is expressed and characterized for antigen binding affinity.

In further embodiments, the relative abundance of VH and VL cDNA in B cells from lymphoid tissues after immunization is used to identify antigen-specific antibodies. Following immunization, adaptive immune responses result in the production of antigen-specific antibodies by newly differentiated B cells. The inventors have found that V gene cDNAs that encode antigen specific antibodies are expressed at very high level in lymphoid tissues. Thus, the inventors have employed high throughput DNA sequencing to determine the V genes expressed by B cells in a particular lymphoid compartment and then deduce the abundance or frequency of these V genes. The inventors synthesized highly abundant V genes and paired VH and VL genes according to their abundance or to their rank-order abundance in that tissue. The inventors have found that between 40% and >80% of the paired V genes give rise to antigen specific antibodies. The percentage of antigen specific antibodies thus produced correlates to the serum titer of antibodies as determined by dilution series of ELISA assays on plated coated with immobilized antigen.

Pairing of V_(H) and V_(L) chains can also be guided by grouping the identified V_(H) and V_(L) sequences into clusters of related sequences (e.g., clusters representing sequences that differ only by somatic hypermutation). Such clustering can be accomplished by producing multiple sequence alignments of the identified V_(H) and V_(L) sequences and thereby clusters of related sequences. Clustering information can then be used to guide V_(H) and V_(L) chaining pairing. Alternatively or additionally, V_(H) and V_(L) chains identified by the instant methods can be screened by a combinatorial affinity assay (e.g., ELISA) to identified paired chains. These methods may be of particular use in situations where an antibody repertoire is not highly polarized, such as often occurs in samples from sheep, goats and rabbits.

In further embodiments there may be provided methods to identify antigen-specific variable gene sequences directly from lymphoid tissues without separation of B cells. An exemplary embodiment may be illustrated in FIG. 2. One or more of the steps may be optional and variations of the steps may be used to carry out the same purpose. First the process may begin with the sacrifice of an immunized animal and the collection of primary, secondary or tertiary lymphoid organs or tissue sample. Second, high-throughput sequencing like NextGen sequencing of V gene cDNAs may be carried out. Third, bioinformatic analysis may be employed to determine the frequency of occurrence of the various V genes. Fourth, V genes expressed at high abundance or frequency could be identified. For example, each of these high abundance (i.e., frequency) genes comprises at least 0.5% of the entire V gene population obtained or analyzed from the corresponding tissue. Fifth, synthetic DNA encoding the abundant genes from above may be prepared. Sixth, the genes encoding the V_(H) and V_(L) chains may be paired based on their ranked-ordered abundance. Seventh, the respective V_(H)-V_(L) gene combinations may be expressed in a host cell to produce antibodies specific to the antigen used for animal immunization.

II. Definitions

Unless defined otherwise, all technical and scientific terms used herein have the meaning commonly understood by one of ordinary skill in the art relevant to the invention. The definitions below supplement those in the art and are directed to the embodiments described in the current application.

The term “antibody” is used herein in the broadest sense and specifically encompasses at least monoclonal antibodies, polyclonal antibodies, multi-specific antibodies (e.g. bispecific antibodies), naturally polyspecific antibodies, chimeric antibodies, humanized antibodies, human antibodies, and antibody fragments. An antibody is a protein comprising one or more polypeptides substantially or partially encoded by immunoglobulin genes or fragments of immunoglobulin genes. The recognized immunoglobulin genes include the kappa, lambda, alpha, gamma, delta, epsilon and mu constant region genes, as well as myriad immunoglobulin variable region genes.

“Antibody fragments” comprise a portion of an intact antibody, for example, one or more portions of the antigen-binding region thereof. Examples of antibody fragments include Fab, Fab′, F(ab′)2, and Fv fragments, diabodies, linear antibodies, single-chain antibodies, and multi-specific antibodies formed from intact antibodies and antibody fragments.

An “intact antibody” is one comprising full-length heavy- and light-chains and an Fc region. An intact antibody is also referred to as a “full-length, heterodimeric” antibody or immunoglobulin.

The term “variable” refers to the portions of the immunoglobulin domains that exhibit variability in their sequence and that are involved in determining the specificity and binding affinity of a particular antibody.

As used herein, “antibody variable domain,” refers to a portion of the light and heavy chains of antibody molecules that include amino acid sequences of Complementary Determining Regions (CDRs; i.e., CDR1, CDR2, and CDR3), and Framework Regions (FRs; i.e., FR1, FR2, FR3, and FR4). FR include those amino acid positions in an antibody variable domain other than CDR positions as defined herein. VH refers to the variable domain of the heavy chain. VL refers to the variable domain of the light chain.

As used herein, the term “complementary nucleotide sequence” refers to a sequence of nucleotides in a single-stranded molecule of DNA or RNA that is sufficiently complementary to that on another single strand to specifically hybridize to it with consequent hydrogen bonding.

An “expression vector” is intended to be any nucleotide molecule used to transport genetic information.

III. Antibody Variable Domains

Certain aspects of the invention provide methods for identifying antibody variable domains or variable domain-coding sequences that are over-represented in serum or B cells. Such skewed representation of antibody variable domains is useful to identify novel antigen binding molecules having high affinity or specificity. Generating antibody or antibody fragments having variable domains with a high level of abundancy allows for the isolation of high affinity binders. The present invention is based, in part, on the discovery that abundancy levels of regions of an antibody variable domain that form the antigen binding pocket, for example CDR3 regions, could correlate with the desired affinity or specificity.

For identifying desired antibody variable domains, certain aspects of the present invention provide methods of determining sequences and distribution of antibody complementarity determining regions (CDRs). Specifically, the sequences of one to six of the complementary determining regions (CDRs) on VH and/or VL could be determined by protein sequencing or nucleic acid sequencing methods. The level of abundancy of variable domains or CDRs could be determined as an absolute level like a concentration or relative level like a rank-order.

Antibodies are globular plasma proteins (˜150 kDa) that are also known as immunoglobulins. They have sugar chains added to some of their amino acid residues. In other words, antibodies are glycoproteins. The basic functional unit of each antibody is an immunoglobulin (Ig) monomer (containing only one Ig unit); secreted antibodies can also be dimeric with two Ig units as with IgA, tetrameric with four Ig units like teleost fish IgM, or pentameric with five Ig units, like mammalian IgM.

The Ig monomer is a “Y”-shaped molecule that consists of four polypeptide chains; two identical heavy chains and two identical light chains connected by disulfide bonds. Each chain is composed of structural domains called Ig domains. These domains contain about 70-110 amino acids and are classified into different categories (for example, variable or IgV, and constant or IgC) according to their size and function. They have a characteristic immunoglobulin fold in which two beta sheets create a “sandwich” shape, held together by interactions between conserved cysteines and other charged amino acids.

There are five types of human Ig heavy chain denoted by the Greek letters: α, δ, ε, γ, and μ. The type of heavy chain present defines the class of antibody; these chains are found in IgA, IgD, IgE, IgG, and IgM antibodies, respectively. Distinct heavy chains differ in size and composition; Ig heavy chains α and γ contain approximately 450 amino acids, while μ and ε have approximately 550 amino acids. Other animals encode analogous immunoglobulin heavy chain classes.

Each heavy chain has two regions, the constant region and the variable region. The constant region is identical in all antibodies of the same isotype, but differs in antibodies of different isotypes. Heavy chains γ, α and δ have a constant region composed of three tandem (in a line) Ig domains, and a hinge region for added flexibility; heavy chains μ and ε have a constant region composed of four immunoglobulin domains. The variable region of the heavy chain differs in antibodies produced by different B cells, but is the same for all antibodies produced by a single B cell or B cell clone. The variable region of each heavy chain is approximately 110 amino acids long and is composed of a single Ig domain.

In humans (and mice) there are two types of Immunoglobulin light chain, which are called lambda (λ) and kappa (κ). A light chain has two successive domains: one constant domain and one variable domain. The approximate length of a light chain is 211 to 217 amino acids. Each antibody contains two light chains that are always identical; only one type of light chain, κ or λ, is present per antibody in these species.

The fragment antigen-binding (Fab fragment) is a region on an antibody that binds to antigens. It is composed of one constant and one variable domain of each of the heavy and the light chain. These domains shape the paratope—the antigen-binding site—at the amino terminal end of the monomer.

The two variable domains bind the epitope on their specific antigens. The variable domain is also referred to as the F_(V) region and is the most important region for binding to antigens. More specifically variable loops, three each on the light (V_(L)) and heavy (V_(H)) chains are responsible for binding to the antigen. These loops are referred to as the Complementarity Determining Regions (CDRs).

A complementarity determining region (CDR) is a short amino acid sequence found in the variable domains of antigen receptor (e.g. immunoglobulin and T cell receptor) proteins that complements an antigen and therefore provides the receptor with its specificity for that particular antigen. CDRs are supported within the variable domains by conserved framework regions (FRs).

Each polypeptide chain of an antigen receptor contains three CDRs (CDR1, CDR2 and CDR3). Since the antigen receptors are typically composed of two polypeptide chains, there are six CDRs for each antigen receptor that can come into contact with the antigen (each heavy and light chain contains three CDRs), twelve CDRs on a single antibody molecule and sixty CDRs on a pentameric IgM molecule. Since most sequence variation associated with immunoglobulins and T cell receptors are found in the CDRs, these regions are sometimes referred to as hypervariable domains. Among these, CDR3 shows the greatest variability as it is encoded by a recombination of the VJ (VDJ in the case of heavy chain) regions.

IV. Antibody Variable Region Analysis

In certain aspects of the invention, antibody variable gene (V gene) sequences derived from cDNA may be analyzed. For example, information from such analysis may be used to generate a database of the V genes (V gene database) that give rise to circulating antibodies so that mass spectrometry (MS) spectra of peptides derived from serum antibodies can be assigned and in turn used to identify the respective full length V genes in the database encoding those peptides. In another embodiment, the sequence information may be used to identify abundant variable gene nucleic acids such as mRNA transcripts and generate antibody or antibody fragments based on the abundant variable genes. The abundant variable genes so identified may correspond to antibodies or antibody fragments that have desired specificity or affinity.

From the nucleotide sequences determined by the initial sequencing, putative amino acid sequences for the VH and VL regions can be determined using standard algorithms and software packages (e.g. see the world wide web at mrc-lmb.cam.ac.uk/pubseq/, the Staden package and Gap4 programs). These can be further characterized to determine the CDR (Complementarity Determining Region) parts of the VH and VL sequences, particularly CDR1, CDR2 and CDR3. Methods for determining the putative amino acid sequences and identifying CDR regions are well known in the art. In one particular embodiment, CDR3 sequences are identified by searching for highly conserved sequence motif at the N-terminal region preceding the CDR3. This method could correctly identified >90% of the CDR3 sequences in antibodies. The putative amino acid sequence derived based on the nucleic acid sequencing of B cell cDNA could be used for the shot gun proteomic analysis of serum antibodies in some embodiments.

A variety of methods have been developed for the immortalization or cloning of antibodies from individual B cells. These techniques include hybridoma technology, memory B cell immortalization by viral (EBV) infection, the engineering of memory B cells that express both surface and secreted antibodies, and the cloning of antigen-specific, antibody genes from transient ASC populations, from memory B cells or from splenic plasma cells. Recently microfluidic and nanopatterning devices have been used to increase the throughput of B cells interrogated for antigen binding and for the subsequent cloning of the V_(H) and V_(L) genes.

While invaluable for the isolation of monoclonal antibodies, these techniques have several drawbacks: First, most have focused on and, in some cases, are only compatible with certain stages of the B cell life cycle. Thus, extensive studies on terminally differentiated mature plasma ASC have not been done. This leaves unresolved the central issue of whether a particular antibody isolated from B cells is represented at a significant amount in the serum of that individual. Also, there is evidence that plasma cells in the bone marrow are the main compartment for antibody synthesis and are selected on the basis of their affinity and perhaps protective function. Second, single B cell cloning methods are still not efficient enough to provide complete information on the diversity of antibodies in serum, especially with respect to serum concentration and abundancy of specific antibody clones. Third, current attempts to pool recombinant mAbs in order to reconstitute a polyclonal antibody that displays higher therapeutic efficacy cannot possibly capture the true protective effect of sera since the mixing of cloned antibodies is completely ad hoc. The present invention could avoid one or more of these problems by the methods described herein.

In certain embodiments, the mRNA from B cells or directly from one or more lymphoid tissues could be isolated and converted to cDNA. In further embodiments, the cDNA may be subject to V_(H) and V_(L) gene isolation. For example, the genes encoding for the variable heavy and the variable light (V_(H) and Vκ, λ) genes could be amplified using specific primers that hybridize to the 5′ and 3′ ends of the cDNA. Depending on the primers used for cDNA construction, V genes of different Ig classes could be distinguished. For example, the V_(H) and V_(L) gene isolation may be based on Ig classes either by using known primer sets of variable gene amplification or, preferably by 3′ RACE (rapid amplification of cDNA ends) using a class-specific 3′ primer. For example, the class-specific 3′ primer may hybridize to the C_(H2) domain.

V. Lymphoid Tissues

In certain embodiments, there may be provided methods of identifying antigen-specific variable region sequences by obtaining nucleic acid sequences directly from lymphoid tissues. In optional aspects, B cells may not be separated from the lymphoid tissue where the B cells reside. The method may comprise isolation of primary, secondary, or tertiary lymphoid tissues. Any methods known for isolation of lymphoid tissues may be used.

Lymphoid tissue associated with the lymphatic system is concerned with immune functions in defending the body against the infections and spread of tumors. It consists of connective tissue with various types of white blood cells enmeshed in it, most numerous being the lymphocytes.

The lymphoid tissue may be primary, secondary, or tertiary depending upon the stage of lymphocyte development and maturation it is involved in. (The tertiary lymphoid tissue typically contains far fewer lymphocytes, and assumes an immune role only when challenged with antigens that result in inflammation. It achieves this by importing the lymphocytes from blood and lymph.

The central or primary lymphoid organs generate lymphocytes from immature progenitor cells. The thymus and the bone marrow constitute the primary lymphoid tissues involved in the production and early selection of lymphocytes.

Secondary or peripheral lymphoid organs maintain mature naive lymphocytes and initiate an adaptive immune response. The peripheral lymphoid organs are the sites of lymphocyte activation by antigen. Activation leads to clonal expansion and affinity maturation. Mature Lymphocytes recirculate between the blood and the peripheral lymphoid organs until they encounter their specific antigen.

Secondary lymphoid tissue provides the environment for the foreign or altered native molecules (antigens) to interact with the lymphocytes. It is exemplified by the lymph nodes, and the lymphoid follicles in tonsils, Peyer's patches, spleen, adenoids, skin, etc. that are associated with the mucosa-associated lymphoid tissue (MALT).

A lymph node is an organized collection of lymphoid tissue, through which the lymph passes on its way to returning to the blood. Lymph nodes are located at intervals along the lymphatic system. Several afferent lymph vessels bring in lymph, which percolates through the substance of the lymph node, and is drained out by an efferent lymph vessel.

The substance of a lymph node consists of lymphoid follicles in the outer portion called the “cortex”, which contains the lymphoid follicles, and an inner portion called “medulla”, which is surrounded by the cortex on all sides except for a portion known as the “hilum”. The hilum presents as a depression on the surface of the lymph node, which makes the otherwise spherical or ovoid lymph node bean-shaped. The efferent lymph vessel directly emerges from the lymph node here. The arteries and veins supplying the lymph node with blood enter and exit through the hilum.

Lymph follicles are a dense collection of lymphocytes, the number, size and configuration of which change in accordance with the functional state of the lymph node. For example, the follicles expand significantly upon encountering a foreign antigen. The selection of B cells occurs in the germinal center of the lymph nodes.

Lymph nodes are particularly numerous in the mediastinum in the chest, neck, pelvis, axilla (armpit), inguinal (groin) region, and in association with the blood vessels of the intestines.

VI. B Cell Sample Preparation

In certain embodiments, B cells may be extracted for isolation of variable region nucleic acid sequences. In other embodiments, B cells may not need to be separated from a lymphoid tissue, thus saving cost and time for B cell isolation. Without B cell separation, lymphoid tissues may be directed used to obtain a pool of antibody variable gene sequences, for example, by using antibody-specific primers or probes, such as primer or probes based on antibody constant region sequences.

In one embodiment, mature, circulating B-cells (memory cells and/or antigen secreting cells (ASCs)) in peripheral blood (for example, about or at least or up to 3, 4, 5, 6, 7, 8, 9, 10, 15, 20 ml or any ranges derivable therefrom) may be used. The circulating B cells may be separated by magnetic sorting protocols (Jackson et al., 2008; Scheid et al., 2009; Smith et al., 2009; Kwakkenbos et al., 2010) as described in the Examples. Alternatively, plasma cells which are terminally differentiated B cells that reside in the bone marrow, spleen or in secondary lymphoid organs could be isolated and used for the determination of the B cell repertoire in an individual animal or human. In particular aspects, plasma cells could be mobilized from the bone marrow into circulation, e.g., by administration of G-CSF (granulocyte colony-stimulating factor) and isolated.

ASC are terminally or near terminally differentiated B cells (including plasma cells and plasmablasts) that are demarcated by the surface markers (for example, syndecan-1). They lack surface IgM and IgD, other typical B cell surface markers (e.g., CD19) and importantly, they express the repressor Blimp-1, the transcription factor Xbp-1 and down-regulate Pax-5. Antibody secreting cells can be generated from: (i) B1 cells which produce low specificity “innate-like” IgM, (ii) from B cells that do not reside in the follicles of lymphoid organs (extrafollicular) and include marginal zone (MZ, IgM⁺, IgD⁺, CD27⁺⁾ cells which generally produce lower affinity antibodies (the latter mostly in the absence T-cell help), and finally, (iii) cells of the B2 lineage that have circulated through the lymphoid follicles. B2 cells progress to the plasma stage either directly from the germinal centers where they undergo selection for higher antigen affinity (following somatic hypermutation) or after they have first entered the memory compartment. Regardless of their precise origin, these cells express high affinity antibodies predominantly of the IgG isotype and constitute the major component of the protective immune response following challenge.

Plasma cells are typically unable to proliferate or de-differentiate back to earlier B cell lineages. Most plasma cells are short-lived and die within a few days. In contrast, a fraction of the plasma cells occupy “niches’ (primarily in bone marrow) that provide an appropriate cytokine microenvironment for survival and continued antibody secretion that may last from months to years; i.e., these are the cells that produce antibodies primarily involved with protection to re-challenge and constitute the “humoral memory” immune response.

A particularly preferred site for ASC isolation is the bone marrow where a large number of plasma cells that express antibodies specific for the antigen are found. It should be noted that B cells that mature to become plasma cells and to reside in the bone marrow predominantly express high affinity IgG antibodies. Mature plasma cells in the bone marrow are selected using based on cell surface markers well known in the field, e.g., CD138⁺⁺, CXCR4⁺ and CD45^(−/weak). Mature plasma cells can also be isolated based on the high expression level of the transcription factor Blimp-1; methods for the isolation of Blimp-1^(high) cells, especially from transgenic animals carrying reporter proteins linked to Blimp-1 are known in the art.

On the other hand, memory B cells are formed from activated B cells that are specific to the antigen encountered during the primary immune response. These cells are able to live for a long time, and can respond quickly following a second exposure to the same antigen. In wake of first (primary response) infection involving a particular antigen, the responding naïve (ones which have never been exposed to the antigen) cells proliferate to produce a colony of cells, most of which differentiate into the plasma cells, also called effector B cells (which produce the antibodies) and clear away with the resolution of infection, and the rest persist as the memory cells that can survive for years, or even a lifetime.

VII. Nucleic Acid Sequencing

Any sequencing methods, particularly high-throughput sequencing methods, may be used to determine one or more of the VH and VL nucleotide sequences in the B cell repertoire. For example, the nucleotide sequence of the VH and VL could be determined by 454 sequencing (Fox et al., 2009) with a universal primer and without amplification to allow accurate quantitation of the respective mRNAs. Reads longer than 300 bp may be processed for further analysis (Weinstein et al., 2009). Non-limiting examples of high-throughput sequencing technologies are described below.

High-throughput sequencing technologies are intended to lower the cost of DNA sequencing beyond what is possible with standard dye-terminator methods. Most of such sequencing approaches use an in vitro cloning step to amplify individual DNA molecules, because their molecular detection methods are not sensitive enough for single molecule sequencing. Emulsion PCR isolates individual DNA molecules along with primer-coated beads in aqueous droplets within an oil phase. Polymerase chain reaction (PCR) then coats each bead with clonal copies of the DNA molecule followed by immobilization for later sequencing. Emulsion PCR is used in the methods by Marguilis et al. (commercialized by 454 Life Sciences), Shendure and Porreca et al. (also known as “Polony sequencing”) and SOLiD sequencing, (developed by Agencourt, now Applied Biosystems). Another method for in vitro clonal amplification is bridge PCR, where fragments are amplified upon primers attached to a solid surface, used in the Illumina Genome Analyzer. The single-molecule method developed by Stephen Quake's laboratory (later commercialized by Helicos) is an exception: it uses bright fluorophores and laser excitation to detect pyrosequencing events from individual DNA molecules fixed to a surface, eliminating the need for molecular amplification.

In parallelized sequencing, DNA molecules are physically bound to a surface, and sequenced in parallel. Sequencing by synthesis, like dye-termination electrophoretic sequencing, uses a DNA polymerase to determine the base sequence. Reversible terminator methods (used by Illumina and Helicos) use reversible versions of dye-terminators, adding one nucleotide at a time, detect fluorescence at each position in real time, by repeated removal of the blocking group to allow polymerization of another nucleotide. Pyrosequencing (used by 454) also uses DNA polymerization, adding one nucleotide species at a time and detecting and quantifying the number of nucleotides added to a given location through the light emitted by the release of attached pyrophosphates.

Sequencing by ligation uses a DNA ligase to determine the target sequence. Used in the polony method and in the SOLiD technology, it uses a pool of all possible oligonucleotides of a fixed length, labeled according to the sequenced position. Oligonucleotides are annealed and ligated; the preferential ligation by DNA ligase for matching sequences results in a signal informative of the nucleotide at that position.

In microfluidic Sanger sequencing the entire thermocycling amplification of DNA fragments as well as their separation by electrophoresis is done on a single glass wafer (approximately 10 cm in diameter) thus reducing the reagent usage as well as cost.

Sequencing by hybridization is a non-enzymatic method that uses a DNA microarray. A single pool of DNA whose sequence is to be determined is fluorescently labeled and hybridized to an array containing known sequences. Strong hybridization signals from a given spot on the array identifies its sequence in the DNA being sequenced. Mass spectrometry may be used to determine mass differences between DNA fragments produced in chain-termination reactions.

DNA sequencing methods currently under development include labeling the DNA polymerase (Scheid et al., 2009), reading the sequence as a DNA strand transits through nanopores, and microscopy-based techniques, such as atomic force microscopy (AFM) or electron microscopy that are used to identify the positions of individual nucleotides within long DNA fragments (>5,000 bp) by nucleotide labeling with heavier elements (e.g., halogens) for visual detection and recording.

The inventors found that less than 10⁵ reads for each of the VH and VL pools could be sufficient to provide information on the variable gene sequences that correspond to the most abundant antibodies found in serum.

VIII. Sequence Abundancy Determination

Bioinformatic methods for the automated analysis of sequencing results such as 454 reads, statistical sequencing error analysis and finally identification and classification of CDRs, especially of CDR3, the most hypervariable region in antibodies have been developed by the inventors.

In certain embodiments, for example to account for sequencing/PCR uncertainties, antibody sequences, particularly CDR3 sequences, could be grouped into families, with each family consisting of all the CDR3 sequences differing by one or two nucleotides or amino acids.

For example, the abundancy level of antibody variable region sequences may be based on the CDR3 sequences as identifiers. The sequences for determination of a level of abundancy may be a family including an identical CDR3 sequence (amino acid sequence or nucleic acid sequence) and a CDR3 sequence having at least 80% homology, for example 85, 90, 95, 96, 97, 98 or 99% homology therewith. Sequence homology is as determined using the BLAST2 program (Tatusova et al., 1999) at the National Center for Biotechnology Information, USA (world wide web at.ncbi.nlm.nih.gov) with default parameters. For example, the sequences occurring in total at a relative level of abundancy represented by a frequency at least 1 percent in the set of sequences may be a combination of the CDR3 sequences or a sequence having 1 or 2 amino acid changes therefrom. For example, a first sequence may occur at a frequency of 0.7 percent, and second, third and fourth sequences each having a single amino acid change therefrom each occur at a frequency of 0.1%—the total occurrence in abundancy is therefore 1.1% and the dominant antibody sequence (occurring at a frequency of 0.7%) is therefore a candidate CDR3 sequence that could be used for antibody generation/characterization.

IX. Use of Antibody Variable Sequence Information

In addition to providing a reference database for interpreting mass spectra data of serum antibody analysis, the nucleic acid information through analysis of the variable region especially CDR sequence and abundancy could also be used to provide potential antigen-specific antibody or antibody fragments. In certain aspects, the resulting V_(H) and Vκ, λ libraries based on the abundant variable region especially CDR information could be inserted into an appropriate expression vector suitable for the production of either full length IgG proteins or of antibody fragments (scFv or Fab or single domain antibodies comprising of only the V_(H) or the Vκ, λ chain). Libraries comprising of V_(H) and Vκ, λ could result in combinatorial pairing of the heavy and light chains.

Some of the randomly paired V_(H) and Vk, λ chains may be active while others will not give rise to functional antibodies. However the inventors have found that because of the very high representation of antigen specific plasma cells in bone marrow, a very large fraction of the resulting clones express functional and high affinity recombinant antibodies. In one example a scFv library constructed from V_(H) and Vκ, λ genes isolated from bone marrow plasma cells >5% of the clones contained antigen specific antibodies.

For example, the inventors analyzed V_(H) and V_(L) transcript levels in bone marrow plasma cells isolated 5 days after booster immunization (incomplete Freund's adjuvant) with 4 different protein antigens in two mice each. Patterns of V-D-J usage and somatic hypermutation were determined and correlated with representation within the bone marrow plasma cell population. Consistent with the pivotal role of bone marrow plasma cells on antibody secretion, antigen specific V_(H) and V_(L) cDNAs were found to be highly enriched to levels between 1-20% of the total Ig RNA. For each of the four antigens tested, 2-4 V_(H) and V_(L) cDNAs were represented at frequencies >4% of the total V_(H) cDNA pool. The four most abundant V_(H) and V_(L) genes for each antigen and from each mouse were synthesized, the heavy and light chains paired as discussed below, and the resulting antibody fragments were expressed in bacteria. Importantly, on average, >80% of the antibody fragments corresponding to the most highly expressed V_(H) and V_(L) genes in the immunized animals were found to be antigen specific by ELISA (enzyme-linked immunosorbent assay) and BIACore analysis.

Thus, the inventors have found that manual ELISA screening of a few hundred clones from such libraries is sufficient to allow the generation of antibodies with high affinity and specificity. Manual ELISA screening of additional clones can be used to reveal different combinations of V_(H) and Vκ, λ genes that give rise to a diverse set of antibodies. This method is simple and fast and the inventors believe that is likely to replace the hybridoma technology for the isolation of antibodies from animals.

X. Quantitative Serum Antibody Analysis

To identify a pool of abundant amino acid sequences of CDR regions, especially CDR3 regions of circulating antibodies, MS shotgun proteomics or protein sequencing methods may be used to determine the amino acid sequences.

Any protein sequencing methods determining the amino acid sequences of its constituent peptides may be used. The two major direct methods of protein sequencing are mass spectrometry and the Edman degradation reaction. It is also possible to generate an amino acid sequence from the DNA or mRNA sequence encoding the protein, if this is known. However, there are also a number of other reactions which can be used to gain more limited information about protein sequences and can be used as preliminaries to the aforementioned methods of sequencing or to overcome specific inadequacies within them.

For example, shotgun proteomic strategy based on digesting proteins into peptides and sequencing them using tandem mass spectrometry and automated database searching could be the method of choice for identifying serum antibody sequences. “Shotgun proteomics” refers to the direct analysis of complex protein mixtures to rapidly generate a global profile of the protein complement within the mixture. This approach has been facilitated by the use of multidimensional protein identification technology (MudPIT), which incorporates multidimensional high-pressure liquid chromatography (LC/LC), tandem mass spectrometry (MS/MS) and database-searching algorithms.

A. IgG Fractionation

Ig proteins of a particular class could be isolated, for example, by affinity chromatography using protein A (or anti-IgA and anti-IgM antibodies for affinity purification of the other major Ig classes).

In certain aspects, antibodies or antibody fragments such as FAB fraction from digestion of purified Igs with papain and FAB purification, could be affinity enriched for binding to desired antigen or pathogen (e.g., a cancer cell, a tumor antigen, or an infection agent), or host tissue for the isolation of antibodies suspected to have a role in autoimmunity. Antibodies may be eluted under denaturing conditions. In further embodiments, several fractions or pools of serum-derived FABs could be generated, including those that are: (a) enriched for antigen, (b) enriched for host tissue and (c) antibodies with unrelated or unknown specificities.

B. Proteolytic Fragmentation

For quantitative shotgun proteomics mass spectrometry analysis, antibodies or antibody fragments such as FAB could be digested using proteases that cleave after amino acids/amino acid pairs that are under-represented in CDR3 but present in the adjacent framework regions. The appropriate proteases for proteomic processing may be identified by bioinformatics analysis of the V gene sequence database.

In one example the FAB fractions are subjected to proteolysis with sequencing grade trypsin (Sigma) at 37° C. for 4 hr. As an alternate method, a combination of the proteases GluC (NEB) and LysC (Sigma) could be used in place of trypsin to generate a distinct set of proteolytic peptides that in computational tests provide better coverage of the CDR3s (i.e. so that cleavage occurs at positions flanking the CDR3s and therefore peptides with intact CDR3s are produced).

In certain embodiments, CDR3 peptides could be enriched from unrelated peptides via specific conjugation of the unique Cys at the end of the CDR3 sequence with a thiol specific reagent that allows the purification of such peptides.

The inventors have developed protocols that deploy a combination of appropriate proteases for peptide generation and Cys specific pull down of thiol containing CDR3 peptides which result in a peptide mixture comprising of at least 30% CDR3 peptide sequences. In one example, CDR3 peptides are enriched via reversible thiol specific biotinylation. In another example, CDR3 peptides are reacted with special chromophores that allow their specific excitation and detection during MS analysis. As the CDR3 peptides almost universally (>99%) contain cysteine, a biotinylated thiol-specific cross-linking agent is used to affinity isolate these peptides for mass spectral analysis thus greatly simplifying the complexity of the spectra.

C. Shotgun MS (Mass Spectrometry) Proteomics

In certain exemplary aspects, the peptides of antibody molecules could be resolved by reverse phase chromatography and in-line nanoelectrospray ionization/high-resolution tandem mass spectrometry, using well-established protocols (Ong and Mann, 2005; Pandey and Mann, 2000; Shevchenko et al., 1996; Hunt et al., 1986; Link et al., 1999; Washburn et al., 2001; Lu et al., 2007) and Fourier-transform LTQ-Orbitrap mass spectrometry (Hu et al., 2005) to collect hundreds of thousands of tandem mass spectra from CDR3 and other FAB-derived peptides.

For example, peptides are separated on a reverse phase Zorbax C-18 column (Agilent) running an elution gradient from 5% to 38% acetonitrile, 0.1% formic acid. Peptides were eluted directly into an LTQ-Orbitrap mass spectrometer (Thermo Scientific) by nano-electrospray ionization. Data-dependant ion selection could be enabled, with parent ion mass spectra (MS1) collected at 100 k resolution. Ions with known charge >+1 may be selected for CID fragmentation spectral analysis (MS2) in order to decrease intensity, with a maximum of 12 parent ions selected per MS1 cycle. Dynamic exclusion is activated, with ions selected for MS2 twice within 30 sec. Ions identified in an LC-MS/MS run as corresponding to peptides from the constant regions of the heavy and light chains may be excluded from data-dependent selection in subsequent experiments in order to increase selection of peptides from the variable region.

D. MS Proteomic Data Analysis

The variable gene sequencing data from B cells of the same subject are employed to supplement the protein sequence database for interpreting peptide mass spectra in shotgun proteolysis (Marcotte, 2007). With the aid of the sample-specific sequence database, we identify CDR3 peptides from the tandem mass spectra (controlling for false discovery rate using standard methods (Keller et al., 2002; Nesvizhskii et al., 2009).

Several recent advances in shotgun proteomics enable protein quantification to ˜2-fold absolute accuracy without introducing additional requirements for isotope labels or internal calibrant peptides (Lu et al., 2007; Malmstrom et al., 2009; Silva et al., 2006a; Vogel and Marcotte, 2008; Ishihama et al., 2005; Liu et al., 2004). Among these approaches, two are well-suited to quantification of individual IgGs: the APEX approach is based upon weighted counts of tandem mass spectra affiliated with a protein (the weighting incorporates machine learning estimates of peptide observability (Lu et al., 2007; Vogel, 2008), and the average ion intensity approach, based on mass spectrometry ion chromatogram peak volumes (Silva et al., 2006a). For example, both methods could be employed to measure abundances of each of the identified antigen-specific IgGs in the serum-containing sample. Combinations (Malmstrom et al., 2009) and single peptide quantitation methods could also be used as alternatives. Algorithms for subtraction of non-CDR3 peptides could be used. On the basis of these measured abundances, at least the 50 or 100 most highly abundant V_(H) and V_(L) proteins in the sample could be rank-ordered.

For example, sample-specific protein sequence databases are created from high-throughput V region cDNA transcript data. V_(H) and V_(L) gene represented by >8 reads by 454 sequencing are compiled into a database which in turn is added to a concatenated forward/reversed-sequence protein-coding database. The LC-MS/MS data is searched against this database using the Sequest search algorithm as part of the Bioworks software package (Thermo Scientific). Filters are applied to ensure high confidence peptide identifications as follows: ΔCN ≧0.250; XCorr=2.0, 2.5, and 3.0 for +2, +3, and ≧+4 charge; and accuracy ≦10.0 ppm.

In certain embodiments, the amino acid sequence analysis coupled with the information various V gene pools of different B cell source (e.g., the particular organ-specific ASC population that expresses V_(H) and V_(L) genes whose products are found in serum) could be employed to identify whether a particular serum antibody originated preferentially in the bone marrow, in secondary lymphoid tissues (as is likely to be the case early in the immune response), or in the case of persistent infection, possibly in tertiary lymphoid tissues. The possibility that a particular antibody is secreted by plasma cells that have migrated to different tissues could also be addressed. At a systems level the inventors could employ this information to estimate the contribution of different compartments to humoral immunity in a quantitative fashion and could generate antibody or antibody fragments involved in different stage of immune response.

XI. Antibody Generation and Characterization

Certain embodiments described above lead to the identification and quantitation of abundant serum antibodies of interest or the most abundant variable region sequences in B cells or in a selected lymphoid tissue. Such information may be used to develop antibody or antibody fragments that have desired binding affinity or antigen response. In certain aspects, their binding specificities or therapeutic utility could be evaluated. For example, antibody or antibody fragments which are cytotoxic towards cancer cells could be generated from the abundant serum polyclonal antibody pool. In further embodiments, antibody or antibody specific fragments that are specific for the antigen used to immunize any animal may be provided by analyzing sequence and abundance information of variable region nucleic acids in B cells or directly from lymphoid tissues.

A. Gene Synthesis for Antibody Generation

To generate antibody or antibody fragments with desired binding specificity or property, the V genes could be synthesized, assembled into FAB or IgG and expressed. V_(H) and V_(L) genes may be generated by high throughout gene synthesis based on the sequence information obtained by the methods described above.

For example, automated gene synthesis could be used. Briefly, gene fragments (lengths from 200 to 500 nucleotides) are generated using inside-out nucleation PCR reactions under carefully controlled conditions to ensure construction of the desired final fragment. Subsequently stitch-overlap extension PCR is used to synthesize the gene of interest. The design of these fragments and relevant overlaps is automated, with oligonucleotide synthesizer worklists and robot operation scripts for synthesis and assembly. With the current configuration, a throughput of 48 kilobases is attained per robotic assembly run (4 hours). Alignment of sequences so as to maintain maximal conservation and subsequent “padding” of the sequences at either end to maintain identical length permits the use of a generic overlapping oligonucleotide assembly strategy and also ensures the most oligonucleotide re-use. Currently throughput stands at 50 V_(H) and 50 V_(L) genes (i.e. >38,000 bp of DNA) synthesized and validated for correct ORF by one researcher within a week and at a reagent cost <$2,000.

B. Pairing of V_(H) and V_(L)

For expression, a particular V_(H) has to be paired with cognate V_(L). The pairing problem could be addressed as follows: First the inventors have empirically found that the correct pairings of V_(H) and V_(L)s in a sample correlate well with the rank-ordered abundancy of the proteins in the sample. For example the fifth most abundant V_(H) pairs with the fifth most abundant V_(L). So far with this approach, using V_(H) and V_(L) bioinformatic rank-ordering information for pairing, the inventors have achieved 75% success in pairing V_(H) and V_(L) genes to produce high affinity antigen specific antibodies from four different mice. Further, the inventors have found that even if the optimal VL for pairing is not the one having similar abundancy based on proteomic analysis and because antigen recognition is dominated by the V_(H) sequence, antigen binding could be still observed, albeit with lower affinity.

In certain aspects, VH and VL chains can be identified by grouping together related VH and VL sequences. For example, identified VH and/or VL sequence can be aligned and clustered base on the relatedness of the sequences. For example, each group may comprise antibody sequences that differ from each other only by the result of somatic hypermutation. In some cases, clusters of sequences can be ranked and the rank of the clusters used guide paring between VH and VL sequences.

In still further aspects, VH and VL chains can be paired based combinatorial affinity assays. In this case, VH and VL pairs for testing can be guided by abundance ranking and/or by clustering of related sequences as outlined above.

The pairing could also be addressed or confirmed by other approaches. For example, in situ hybridization (ISH) of fixed plasma cells with V_(H) and candidate V_(L) probes, for example, identified from the abundancy analysis. ISH can easily be applied in a high throughput manner using appropriate robotic automation. Alternatively, ESI-MS (electrospray ionization mass spectrometry) of the FAB pool, coupled with matching of these spectra to the expected molecular weight can in certain cases determine V_(H) and V_(L) pairing.

C. Antibody Expression

In further aspects, the synthesized V_(H) and V_(L) genes may be inserted into appropriate vectors for expression, for example, as FABs in E. coli or as full length IgGs by transient transfection of HEK293 cells.

Binding between candidate antibody or antibody fragments and antigen could be then evaluated by any methods for binding detection and quantification, particularly ELISA. For example, cancer specific antibodies or antibody fragments could be characterized by cancer and host cell binding by fluorescence-activated cell sorting (FACS) following fluorescent labeling of antibodies.

Antibodies according to certain aspects of the invention may be labeled with a detectable label or may be conjugated with an effector molecule, for example a drug e.g., an antibacterial agent or a toxin or an enzyme, using conventional procedures and the invention extends to such labeled antibodies or antibody conjugates.

Antibodies usable or produced in the present invention, may be a whole antibody or an antigen binding fragment thereof and may in general belong to any immunoglobulin class. Thus, for example, it may be an IgM or an IgG antibody. The antibody or fragment may be of animal, for example, mammalian origin and may be for example of murine, rat, sheep or human origin. Preferably, it may be a recombinant antibody fragment, i.e., an antibody or antibody fragment which has been produced using recombinant DNA techniques. Such recombination antibody fragment may comprise prevalent CDR or variable domain sequences identified as above.

Particular recombinant antibodies or antibody fragments include, (1) those having an antigen binding site at least part of which is derived from a different antibody, for example those in which the hypervariable or complementarity determining regions of one antibody have been grafted into the variable framework regions of a second, different antibody (as described in, for example, EP 239400); (2) recombinant antibodies or fragments wherein non-Fv sequences have been substituted by non-Fv sequences from other, different antibodies (as described in, for example, EP 171496, EP 173494 and EP 194276); or (3) recombinant antibodies or fragments possessing substantially the structure of a natural immunoglobulin but wherein the hinge region has a different number of cysteine residues from that found in the natural immunoglobulin but wherein one or more cysteine residues in a surface pocket of the recombinant antibody or fragment is in the place of another amino acid residue present in the natural immunoglobulin (as described in, for example, WO 89/01782 and WO 89/01974).

Teachings of texts such as Harlow and Lane (1998) further details antibodies, antibody fragments, their preparation and use.

The antibody or antibody fragment may be of polyclonal or monoclonal origin. It may be specific for at least one epitope.

Antigen binding antibody fragments include, for example, fragments derived by proteolytic cleavage of a whole antibody, such as F(ab′)2, Fab′ or Fab fragments, or fragments obtained by recombinant DNA techniques, for example Fv fragments (as described, for example, in WO 89/02465).

XII. Therapeutic Applications

The present invention may involve methods that have a wide range of therapeutic applications, such as cancer therapy, enhancing immune response, vaccination, or treatment of infectious disease or autoimmune diseases.

In some embodiments, the present methods may be used for the quantitative molecular deconvolution of antibody response in cancer patients in remission to identify the sequence and abundancy of the highly represented antibodies in circulation that may contribute to the eradication of the tumor in the patient. Such antibodies could be very useful as therapeutic agents on their own or for the identification new antigens on cancer cells that can serve as therapeutic targets. Similarly in some embodiments the present methods can be used to identify antibodies that can protect patients from a particular infectious agent. Such antibodies may be identified either from patients that had been infected and then recovered from the infection or alternatively, from vaccinated patients. These antibodies or antibody fragments could be produced and their specificity and cytotoxicity toward cancer cells or neutralization pitency towards infectious agents could be evaluated. The ability to deconvolute the serum polyclonal response by characterizing the relative abundancy and amino acid sequences of its antibody components and then to individually evaluate cancer cell binding and cytotoxicity could provide an unprecedented wealth of information on the nature of adaptive immune responses to malignancies. Such identified antibodies could lead to discovery of potent cytotoxic cancer therapeutics and the identification of novel tumor antigens used for cancer detection and therapy.

For example, therapeutic antibodies for leukemia via the deconvolution of antibody responses in patients in remission, following allogeneic hematopoietic stem cell (HSC) transplantation could be identified by the methods described above. Promising antibodies could then be taken through pharmacological engineering and animal evaluation.

Certain aspects of the present invention may involve the passive transfer of antibody or antibody fragments generated by certain aspects of the present invention to non-immune individuals (e.g. patients undergoing chemo/radio therapy, immunosuppression for organ transplantation, immunocompromised due to underlying conditions such as diabetes, trauma etc, also the very young or very old). For example, the sequences of antibodies conferring immunity can be determined by looking for over-represented VH and VL sequences in patients who have overcome infection. These protective antibodies can be re-synthesised at the genetic level, over-expressed in E. coli (or other expression systems) and purified. The resultant purified recombinant antibody can then be administered to patients as a passive immunotherapy. Antibodies can also be ordered from commercial suppliers such as Operon Technologies Inc., USA (on the world wide web at operon.com) by simply supplying them with the sequence of the antibody to be manufactured.

Vaccination protects against infection by priming the immune system with pathogen-derived antigen(s). Vaccination is effected by a single or repeated exposures to the pathogen-derived antigen(s) and allows antibody maturation and B cell clonal expansion without the deleterious effects of the full-blown infectious process. T cell involvement is also of great importance in effecting vaccination of patients. Certain aspects of the present invention can also be used to monitor the immunisation process with experimental vaccines along with qualitative and quantitative assessment of antibody response. For example, one or more subjects are given the experimental vaccine and VH and VL sequences are amplified from the subjects and the antibody repertoire analyzed as described above. An increased abundancy of a given antibody variable domain or CDR sequence with vaccination could lead to the identification of a protective antibody candidate pool. After validation, such protective antibodies could be used for treatment of patients in need of such protection, such as patients infected by a microorganism, such as a virus.

XIII. Examples

The following examples are included to demonstrate preferred embodiments of the invention. It should be appreciated by those of skill in the art that the techniques disclosed in the examples which follow represent techniques discovered by the inventor to function well in the practice of the invention, and thus can be considered to constitute preferred modes for its practice. However, those of skill in the art should, in light of the present disclosure, appreciate that many changes can be made in the specific embodiments which are disclosed and still obtain a like or similar result without departing from the spirit and scope of the invention.

Example 1 Immunization Protocol

Protein antigens (e.g., purified human complement protein C1s (CalBiochem), purified chicken egg ovalbumin (OVA, Sigma), or recombinant bacterially-expressed human B cell regulator of IgH transcription (BRIGHT) were resuspended in sterile-filtered phosphate buffered saline (PBS) at 1.0 mg/ml. On the day of primary immunization, 25 μl of antigen solution was thoroughly mixed with 25 μl of Complete Freund's Adjuvant (CFA, Pierce Biotechnology) and 50 μl of sterile PBS and stored on ice. Female Balb/c mice (Charles Rivers Laboratories) 6-8 weeks old were housed in conventional barrier space and were maintained on a normal chow diet. Prior to injections, mice were bled from the tail vein and approximately 25 μl of blood was collected and stored at −20° C. for later analysis. Day 1 was designated as the day primary immunizations were performed. 100 μl of the antigen-CFA mixture per mouse was injected with a 26-gauge needle subcutaneously into the backpad. Mice were monitored daily by animal housing staff and cages were changed twice per week.

For secondary immunization, 25 μl of antigen solution was thoroughly mixed with 25 μl of Incomplete Freund's Adjuvant (IFA, Pierce Biotechnology) and 50 μl of sterile PBS and stored on ice. On day 21 mice were given the secondary immunization intraperitoneally at 100 μl of antigen-IFA mixture per mouse. On day 26 mice were sacrificed by CO₂ asphyxiation and blood, lymph nodes, spleen, femurs and tibia were collected. For 3^(rd) and subsequent immunizations as needed, 25 μl of antigen solution was thoroughly mixed with 25 μl of Incomplete Freund's Adjuvant (IFA, Pierce Biotechnology) in 50 μl of sterile PBS were injected into animals two weeks after secondary immunization and every 2 weeks for subsequent immunizations, as needed.

Example 2 Isolation of the Plasma Cell (CD138⁺CD45R (B220)⁻CD49b⁻) Population from Murine Bone Marrow

The muscle and fat tissue was removed from tibias and femurs harvested from immunized mice. The ends of both tibia and femurs were clipped with surgical scissors and bone marrow was flushed out with a 26-gauge insulin syringe (Becton Dickinson, BD). Bone marrow tissue was collected in sterile-filtered Buffer#1 (PBS/0.1% bovine serum albumin (BSA)/2 mM ethylenediaminetetracetic acid (EDTA)). Bone marrow cells were collected by filtration through a 70-um cell strainer (BD) with mechanical disruption and washed with 20 ml of PBS and collected in a 50 ml tube (Falcon, BD). Bone marrow cells were then centrifuged at 1200 RPM for 10 min at 4° C. Supernatant was decanted and cell pellet was resuspended with 3.0 ml of RBC lysis buffer (eBioscience) and shaken gently at 25° C. for 5 minutes. Cell suspension was then diluted with 20 ml of PBS and centrifuged at 1200 RPM for 10 minutes at 4° C. Supernatant was decanted and cell pellet was resuspended in 1.0 ml of Buffer#1.

Each isolated bone marrow cell suspension was incubated with 7.5 ug and 10 ug of biotinylated rat anti-mouse CD45R (B220) and biotinylated rat anti-mouse CD49b (eBioscience), respectively. In Example 9, each isolated bone marrow cell suspension was incubated with 2.5 ug and 1.5 ug of biotinylated rat anti-mouse CD45R (B220) and biotinylated rat anti-mouse CD49b (eBioscience), respectively. Cell suspension was rotated at 4° C. for 20 minutes. Cell suspensions were then centrifuged at 2,000 RPM for 6 minutes at 4° C., supernatant was removed and the cell pellet was resuspended in 1.5 ml of Buffer#1. Streptavidin conjugated M280 magnetic beads (Invitrogen) were washed and resuspended according to manufacturer's protocol. 50 μl of magnetic beads were added to each cell suspension and the mixture was rotated at 4° C. for 20 min. Cell suspension was then placed on Dynabead magnet (Invitrogen) and the supernatant (negative fraction, cells unconjugated to beads) was collected, cells conjugated to beads were discarded (alternatively, bead bound cells could be saved for later analysis).

Optionally, the negative fraction cells were then incubated with 2.5 μg of both biotinylated rat anti-mouse CD45R (B220) and biotinylated rat anti-mouse CD49b and rotated at 4° C. for 20 min. Cells were then centrifuged at 2,000 RPM at 4° C. for 6 min, supernatant was removed and cell pellet was resuspended in 1.0 ml of Buffer#1. 50 μl of magnetic beads were added to each cell suspension and the mixture was rotated at 4° C. for 20 min. Cell suspension was then placed on Dynabead magnet (Invitrogen) and the supernatant (negative fraction, cells unconjugated to beads) was collected, cells conjugated to beads were discarded (alternatively, bead bound cells could be saved for only analysis).

Pre-washed streptavidin M280 magnetic beads were incubated for 30 min at 4° C. with biotinylated rat anti-mouse CD138 (BD Pharmingen) with 0.75 μg antibody per 25 μl of magnetic beads. Beads were then washed with magnet according to manufacturer's protocol and resuspended in Buffer#1. The negative cell fraction (double-depleted of CD45R/B220⁺ and CD49b⁺ cells) collected previously was incubated with 50 μl of CD138 conjugated magnetic beads and rotated at 4° C. for 30 min. Cells were then placed on magnet and washed 3 times with Buffer#1, the negative (CD138⁻) cells unbound to beads were discarded (or saved only for analysis). The positive CD138⁺ bead-bound cells were collected and stored at 4° C. until further processed.

Flow cytometry analysis of the plasma cell purification process is shown in FIG. 3.

Example 3 Isolation of Antibody Secreting Cells (ASCs) and Memory B Cells

Murine Memory B Cells.

Secondary lymphoid organs (spleen and lymph nodes) are harvested from immunized mice following euthanization. Tissue was collected in sterile-filtered Buffer#1 (PBS/0.1% bovine serum albumin (BSA)/2 mM EDTA). Splenic and lymph node cells were collected by filtration through a 70-um cell strainer (BD) with mechanical disruption and washed with 20 ml of PBS and collected in a 50 ml tube (Falcon, BD). Splenic and lymph node cells were then centrifuged at 1200 RPM for 10 min at 4° C. Supernatant was decanted and cell pellet was resuspended with 3.0 ml of RBC lysis buffer (eBioscience) and shaken gently at 25° C. for 5 minutes. Cell suspension was then diluted with 20 ml of PBS and centrifuged at 1200 RPM for 10 minutes at 4° C. Supernatant was decanted and cell pellet was resuspended in 1.0 ml of Buffer#1.

Additionally whole blood is extracted by cardiac puncture. Whole Blood is added to histopaque solution (Sigma) at 1:1 volume, avoiding mixing of the contents. The blood-histopaque solution is centrifuged at 1,600 RPM for 30 minutes at 23° C. without centrifugation braking. The peripheral blood mononuclear cell (PBMC) layer is isolated following gradient centrifugation, and washed twice through centrifugation with wash buffer (PBS, 2.5% Fetal Bovine Serum (FBS), 1 mM ethylenediaminetetraacetic acid (EDTA)). Cells were then resuspended in Buffer#1.

Splenic or lymph node germinal center cells are labeled with peanut agglutinnan biotin and germinal center memory B cells are then isolated with streptavidin magnetic beads (Invitrogen).

Human ASC and Memory B Cells.

PBMCs from human volunteers are isolated and then stained with fluorescent antibodies. PBMC's are isolated using FACS by gating on CD19high/CD20low/CD3neg and then a second sort on CD27high/CD38high to obtain a pure population of ASC and memory B cells (Wrammert et al., 2008).

Example 4 Preparation of Variable Light (VL) and Variable Heavy (VH) Genes for High-Throughput DNA Sequencing

RNA Isolation

CD138⁺CD45R⁻ bone marrow plasma cells or peripheral ASC and B cells isolated as described in Examples 2 and 3 above were centrifuged at 2,000 RPM at 4° C. for 5 min. Cells were then lysed with TRI reagent and total RNA was isolated according to the manufacturer's protocol in the Ribopure RNA isolation kit (Ambion). mRNA was isolated from total RNA through with oligodT resin and the Poly(A) purist kit (Ambion) according to the manufacturer's protocol. mRNA concentration was measured with an ND-1000 spectrophotometer (Nanodrop).

PCR Amplification

The isolated mRNA was used for first strand cDNA synthesis by reverse transcription with the Maloney murine leukemia virus reverse transcriptase (MMLV-RT, Ambion). For cDNA synthesis, 50 ng of mRNA was used as a template and oligo(dT) primers were used RT-PCR was performed according to manufacturer protocol of Retroscript kit (Ambion). Following cDNA construction, PCR amplification was performed to amplify the VL and VH genes using 2 ul of unpurified cDNA product and established VL and VH degenerate primer mixes (Krebber et al., 1997; Mazor et al., 2007). A complete list of primers can be found in Table 1.

TABLE 1 Primer mixes for PCR amplification of V_(L ) and V_(H) genes SEQ ID Sequence NO: V_(L) -Forward Primers YarivL-FOR1 AGC CGG CCA TGG CGG AYA TCC AGC TGA CTC AGC C 67 YarivL-FOR 2 AGC CGG CCA TGG CGG AYA TTG TTC TCW CCC AGT C 68 YarivL-FOR 3 AGC CGG CCA TGG CGG AYA TTG TGM TMA CTC AGT C 69 YarivL-FOR 4 AGC CGG CCA TGG CGG AYA TTG TGY TRA CAC AGT C 70 YarivL-FOR 5 AGC CGG CCA TGG CGG AYA TTG TRA TGA CMC AGT C 71 YarivL-FOR 6 AGC CGG CCA TGG CGG AYA TTM AGA TRA MCC AGT C 72 YarivL-FOR 7 AGC CGG CCA TGG CGG AYA TTC AGA TGA YDC AGT C 73 YarivL-FOR 8 AGC CGG CCA TGG CGG AYA TYC AGA TGA CAC AGA C 74 YarivL-FOR 9 AGC CGG CCA TGG CGG AYA TTG TTC TCA WCC AGT C 75 YarivL-FOR 10 AGC CGG CCA TGG CGG AYA TTG WGC TSA CCC AAT C 76 YarivL-FOR 11 AGC CGG CCA TGG CGG AYA TTS TRA TGA CCC ART C 77 YarivL-FOR 12 AGC CGG CCA TGG CGG AYR TTK TGA TGA CCC ARA C 78 YarivL-FOR 13 AGC CGG CCA TGG CGG AYA TTG TGA TGA CBC AGK C 79 YarivL-FOR 14 AGC CGG CCA TGG CGG AYA TTG TGA TAA CYC AGG A 80 YarivL-FOR 15 AGC CGG CCA TGG CGG AYA TTG TGA TGA CCC AGW T 81 YarivL-FOR 16 AGC CGG CCA TGG CGG AYA TTG TGA TGA CAC AAC C 82 YarivL-FOR 17 AGC CGG CCA TGG CGG AYA TTT TGC TGA CTC AGT C 83 YarivL-FOR 1 AGC CGG CCA TGG CGG ARG CTG TTG TGA CTC AGG AAT C 84 Lambda V_(L) - Reverse Primers YarivL-REV 1 GAT GGT GCG GCC GCA GTA CGT TTG ATT TCC AGC TTG G 85 YarivL-REV 2 GAT GGT GCG GCC GCA GTA CGT TTT ATT TCC AGC TTG G 86 YarivL-REV 4 GAT GGT GCG GCC GCA GTA CGT TTT ATT TCC AAC TTT G 87 YarivL-REV 5 GAT GGT GCG GCC GCA GTA CGT TTC AGC TCC AGC TTG G 88 YarivL-REV 1 GAT GGT GCG GCC GCA GTA CCT AGG ACA GTC AGT TTG Lambda G 89 YarivL-REV GAT GGT GCG GCC GCA GTA CCT AGG ACA GTG ACC TTG Lambda 2 G 90 V_(H) - Forward Primers YarivH-FOR 1 GTT ATT GCT AGC GGC TCA GCC GGC AAT GGC GGA KGT 91 RMA GCT TCA GGA GTC YarivH-FOR 2 GTT ATT GCT AGC GGC TCA GCC GGC AAT GGC GGA GGT 92 BCA GCT BCA GCA GTC YarivH-FOR 3 GTT ATT GCT AGC GGC TCA GCC GGC AAT GGC GCA GGT 93 GCA GCT GAA GSA STC YarivH-FOR 4 GTT ATT GCT AGC GGC TCA GCC GGC AAT GGC GGA GGT 94 CCA RCT GCA ACA RTC YarivH-FOR 5 GTT ATT GCT AGC GGC TCA GCC GGC AAT GGC GCA GGT 95 YCA GCT BCA GCA RTC YarivH-FOR 6 GTT ATT GCT AGC GGC TCA GCC GGC AAT GGC GCA GGT 96 YCA RCT GCA GCA GTC YarivH-FOR 7 GTT ATT GCT AGC GGC TCA GCC GGC AAT GGC GCA GGT 97 CCA CGT GAA GCA GTC YarivH-FOR 8 GTT ATT GCT AGC GGC TCA GCC GGC AAT GGC GGA GGT 98 GAA SST GGT GGA ATC YarivH-FOR 9 GTT ATT GCT AGC GGC TCA GCC GGC AAT GGC GGA VGT 99 GAW GYT GGT GGA GTC YarivH-FOR 10 GTT ATT GCT AGC GGC TCA GCC GGC AAT GGC GGA GGT 100 GCA GSK GGT GGA GTC YarivH-FOR 11 GTT ATT GCT AGC GGC TCA GCC GGC AAT GGC GGA KGT 101 GCA MCT GGT GGA GTC YarivH-FOR 12 GTT ATT GCT AGC GGC TCA GCC GGC AAT GGC GGA GGT 102 GAA GCT GAT GGA RTC YarivH-FOR 13 GTT ATT GCT AGC GGC TCA GCC GGC AAT GGC GGA GGT 103 GCA RCT TGT TGA GTC YarivH-FOR 14 GTT ATT GCT AGC GGC TCA GCC GGC AAT GGC GGA RGT 104 RAA GCT TCT CGA GTC YarivH-FOR 15 GTT ATT GCT AGC GGC TCA GCC GGC AAT GGC GGA AGT 105 GAA RST TGA GGA GTC YarivH-FOR 16 GTT ATT GCT AGC GGC TCA GCC GGC AAT GGC GCA GGT 106 TAC TCT RAA AGW GTS TG YarivH-FOR 17 GTT ATT GCT AGC GGC TCA GCC GGC AAT GGC GCA GGT 107 CCA ACT VCA GCA RCC YarivH-FOR 18 GTT ATT GCT AGC GGC TCA GCC GGC AAT GGC GGA TGT 108 GAA CTT GGA AGT GTC YarivH-FOR 19 GTT ATT GCT AGC GGC TCA GCC GGC AAT GGC GGA GGT 109 GAA GGT CAT CGA GTC V_(H) - Reverse Primers YarivH-REV 1 CCC TTG AAG CTT GCT GAG GAA ACG GTG ACC GTG GT 110 YarivH-REV 2 CCC TTG AAG CTT GCT GAG GAG ACT GTG AGA GTG GT 111 YarivH-REV 3 CCC TTG AAG CTT GCT GCA GAG ACA GTG ACC AGA GT 112 YarivH-REV 4 CCC TTG AAG CTT GCT GAG GAG ACG GTG ACT GAG GT 113

A 50 ul PCR reaction consisted of 0.2 mM of forward and reverse primer mixes, 5 ul of Thermopol buffer (NEB), 2 ul of unpurified cDNA, 1 ul of Taq DNA polymerase (NEB), and 39 ul of double distilled H2O. The PCR thermocycle program was: 92° C. for 3 min; 4 cycles (92° C. for 1 min, 50° C. for 1 min, 72° C. for 1 min); 4 cycles (92° C. for 1 min, 55° C. for 1 min, 72° C. for 1 min); 20 cycles (92° C. for 1 min, 63° C. for 1 min, 72° C. for 1 min); 72° C. for 7 min; 4° C. storage. PCR gene products were gel purified and submitted to SeqWright (Houston, Tex.) and Genomic Sequencing and Analysis Center at the University of Texas Austin for Roche GS-FLX 454 DNA sequencing.

PCR products of the VL and VH genes were gel purified and submitted to Genomic Sequencing and Analysis Center at the University of Texas Austin for 454 DNA sequencing.

Rapid cDNA End (RACE) Amplification.

Alternatively, a cDNA amplicon library specific for the variable light (VL) and variable heavy (VH) was constructed from the isolated mRNA. To start, first strand cDNA was synthesized from mRNA using the SMARTScribe Maloney murine leukemia virus reverse transcriptase (MMLV-RT, Clonetech). The cDNA synthesis utilized 25 ng mRNA, template switching specific 5′ primers and 3′ gene specific primers. Buffers and reaction conditions were used according to manufacturer's protocol. Primers were used that already incorporated 454 sequencing primers (Roche) on both 5′ and 3′ ends along with multiplex identifiers (MID) so that the cDNA synthesized and amplified could be directly used in the 454 emPCR step. The 5′ forward primer utilized MMLV-RT template switching by the addition of three cytosine residues at the 3′ end of first strand cDNA along with a portion of the 5′ sequencing Primer B of 454 Titanium (SRp#1). For the reverse primer, primers were used to amplify the VL gene and a small portion of the 3′ terminal of the light chain constant region Cκ along with the Primer A of 454 Titanium including 3 unique MIDs (SRp#2, 3, 4). Similarly, VH genes were amplified along with a small portion of the 3′ terminal of the heavy chain constant 1 (CH1) region along with the Primer A of 454 Titatnium including 3 unique MIDs (SRp#5, 6, 7). All primers were synthesized and HPLC purified from Integrated DNA Technologies (IDT) and are listed in Table 2.

TABLE 2 Primers used for VL and VH cDNA amplicon Library Primer Name Sequence 5′ to 3′ SRp#1 TGTGCCTTGGCAGTCTCAGGGG (SEQ ID NO: 1) SRp#2 CCATCTCATCCCTGCGTGTCTCCGACTCAGACGAGTG CGTACAGTTGGTGCAGCATCAGC (SEQ ID NO: 2) SRp#3 CCATCTCATCCCTGCGTGTCTCCGACTCAGACGCTCG ACAACAGTTGGTGCAGCATCAGC (SEQ ID NO: 3) SRp#4 CCATCTCATCCCTGCGTGTCTCCGACTCAGAGACGCA CTCACAGTTGGTGCAGCATCAGC (SEQ ID NO: 4) SRp#5 CCATCTCATCCCTGCGTGTCTCCGACTCAGACGAGTG CGTGATAGACCGATGGGGCTGTTG (SEQ ID NO: 5) SRp#6 CCATCTCATCCCTGCGTGTCTCCGACTCAGACGCTCG ACAGATAGACCGATGGGGCTGTTG (SEQ ID NO: 6) SRp#7 CCATCTCATCCCTGCGTGTCTCCGACTCAGAGACGCA CTCGATAGACCGATGGGGCTGTTG (SEQ ID NO: 7) SRp#8 /5BioTEG/CCTATCCCCTGTGTGCCTTGGCAGTCTC AG (SEQ ID NO: 8) SRp#9 GAGACACGCAGGGATGAGATGG (SEQ ID NO: 9)

Following first strand cDNA synthesis, PCR was performed to amplify cDNA with primers based on the 5′ and 3′ ends of the added 454 sequencing primers (SRp#8 and 9, respectively; note that 5′ forward primer SRp#8 was biotinylated on the 5′ end). Standard PCR conditions were used according to the Advantage 2 PCR kit (Clontech). The cDNA samples were then run on a 1% agarose gel and the bands corresponding to VL or VH at ˜450 and ˜500 bp, respectively were extracted and further purified (Zymogen). cDNA concentration was measured using a nanodrop spectrophotometer. 500 ng of cDNA per sample was then used for 454 sequencing.

High-Throughput Sequencing of V_(L) and V_(H) Repertoires.

V gene repertoires isolated from BM-PC of eight mice were sequenced using high-throughput 454 GS-FLX sequencing (University of Texas, Austin, Tex.; SeqWright, Houston, Tex.). In total, 415,018 sequences were generated, and 454 data quality control filtered and grouped >97% of the sequences into datasets for each mouse according to their Multiplex Identifiers (MID) usages.

Example 5 Analysis of Antibody Variable Heavy and Variable Light Sequences

454 GS-FLX was used to obtain full-length reads of antibody variable regions VL and VH from the bone marrow plasma cells or ACS or memory B cells or directly from isolated bone marrow, lymph nodes or spleen. A full-length read was considered a sequence with coverage of all 3 CDRs.

CDR3s were identified by homology searching of highly conserved four amino acid motifs at N- and C-terminal of CDR3. Table 3 lists the motifs used to identify CDR-L3 and CDR-H3 and their occurrence frequency in KabatMan database (world wide web at bioinf.org.uk).

Reverse complementary sequences were also generated for motif search, and only in-frame CDR3 were considered for the following analysis. The identified CDR3 sequences were used as the VL and VH unique signature identifiers and their relative abundancy was calculated and used to represent corresponding variable gene abundancy (Tables 4-5). The full-length VL and VH sequences carrying the highly abundant CDR3 were then identified by an alignment similarity search and standard BLAST against the dataset (Table 6).

TABLE 3 Conserved motifs used to identify CDR3s N-CDR3H Kabat # 86 90 91 92 Residue Asp Tyr/Phe Tyr/Phe Cys Frequency 98.3% 99.4% 98.8% 99.5% C-CDR3L Kabat # 103 104 106 107 Residue Trp Gly Gly Ser/Thr Frequency 99.4% 98.6% 99.7% 98.7% N-CDR3H Kabat # 82 86 87 88 Residue Asp Tyr Tyr/Phe Cys Frequency 98.5% 98.2% 97.7% 99.1% C-CDR3L Kabat # 98 99 101 102 Residue Phe Gly Gly Thr Frequency 99.5% 99.4% 98.5% 98.1%

TABLE 4 Consensus CDR3H sequences from Bright-1 sample and their occurrence frequency (%) SEQ ID NO: control-1 control-2 C1s-1 C1s-2 Bright-1 Bright-2 HDYGNYVDY 10 0 0 0 0 7.21 0.02 DGNYQEDYFDY 11 0 0 0.02 0 5.62 0 EGYAYDVDY 12 0 0 0 0 1.91 0.01 DDYDWYFDV 13 0.09 2.11 1.97 0.03 1.54 0.01 DNWDWYFDV 14 0.27 0 1.11 0.72 1.48 0.01 DDGYYWYFDV 15 0 2.54 0.01 0 1.26 0 YDYGKDFDY 16 0 0 0 0 1.21 0 CADGNY 17 0 0 0 0 1.07 0 VLGQGDYYAMDY 18 0 0 0 0 0.97 0

TABLE 5 Consensus CDR3H sequences from C1s-2 sample and their occurrence frequency (%) SEQ ID NO: Control-1 control-2 C1s-1 C1s-2 Bright-1 Bright-2 SDRYDGYFDY 19 0 0 0.09 10.98 0.04 0.01 SDRFDGYFDY 20 0 0 0.05 9.93 0.05 0.03 WLLLAY 21 0 0 0 3.33 0.01 0.02 YGNYFDY 22 0.01 0.94 0.35 2.47 0.14 0.58 SDGYYYFDY 23 0 0 0.02 1.66 0 0 SGGNYDAMDY 24 24 0 0 0 1.17 0.02 0 YYDYDKAYYFDY 25 0 0 0.03 1.15 0 0

TABLE 6 Full-length amino acid sequence of consensus VL and VH SEQ ID NO: Full-length amino acid sequence of consensus VL and VH C1s-2.1L 26 DVLMTQTPLSLPVSLGDQASISCRSSQSIVHSNGDTYLEWYLQKPG QSPKLLVYKLSNRFSGVPDRFSGSGSGTDFTLKISRVEAEDLGVYYC FQGSHVPLTFGAGTKLEIK C1s-2.2L 27 DIVMTQSPASLAVSLGQRATISCRASESVDSYGNSFMHWYQQKPG QPPKLLIYRASNLESGIPARFSGSGSRTDFTLTINPVEADDVTTYYCQ QSNEDPWTFGGGTKLEIK C1s-2.3L 28 DIVMTQSPLTLTVTIGQPASISCKSSQSLLDSDGKTYLNWLLQRPGQ SPKRLIYLVSKLDSGVPDRFTGSGSGTEFTLKTSRVEAEDLGVYYC WQGTHFPHFGGGTKLEIK C1s-2.1H 29 QVQLQQSGAELARPGASVKMSCKASGYTFTSYTMHWVKQRPGQG LEWIGYINPSSGYTNYNQKFKDKATLTADKSSSTANMQLSSLTSED SAVYYCARSDRYDGYFDYWGQGTTLTVSSA C1s-2.2H 30 EVKLVESGGGFVKPGGSLKLSCAASGFTFSTYGMSWVRQTPEKRL EWVASISAGGTTYYSDSVKGRFTISRDNARNILYLQMSSLRSEDTA MYYCARWLLLAYWGQGTLVTSSA C1s-2.3H 31 QVQLQQSGTVLARPGASVKMSCKASGYTFTSYWMHWVKQRPGQ GLEWIGAIYPGNSDTSYNQKFKGKAKLTAVTSTSTAYMELSSLTNE DSAVYYCTRSDGYYYFDYWGQGTTLTVSSA Bright-1.1L 32 DIVMTQSPSSLSASLGERVSLTCRASQDIGSSLNWLQQEPDGTIKRLI YATSSLDSGVPKRFSGSRSGSDYSLTISSLESVDFVDYYCLQYASSPF TFGSGTKLEIK Bright-1.2L 33 DIVMTQSPLTLSVTIGQPASISCKSSQSLLDSDGKTYLNWLLQRPGQ SPKRLIYLVSKLDSGVPDRFTGSGSGTDFTLKISRVEAGDLGVYYC WQGTHFPRTFGGGTKLEIK Bright-1.3L 34 DIVMTQSPASLAVSLGQRATISCRASESVDSYGNSFMHWYQQKPG QPPKLLIYLASNLESGVPARFSGSGSRTDFTLTIDPVEADDAVTYYC QQNNEDPRTFGGGTKLEIK Bright-1.4L 35 DIVMTQSPAIMSASPGEKVTITCSASSSVSYMHWFQQKPGTSPKLWI YSTSNLASGVPARFSGSGSGTSYSLTISRVEAEDAATYYCQQRSSYP LTFGAGTKLEIK Bright-1.1H 36 EVKLVESGGDLVKPGGSLKLSCAASGFTFSSYGMSWVRQTPDKRL EWVATISSGGSYTYYPDSVKGRFTISRDNAKNTLYLQMSSLKSEDT AMYYCARHDYGNYVDYWGQGTTLTVSSA Bright-1.2H 37 EVQLVESGGDLVKPGGSLKLSCAASGFTFSSYGMSWVRQTPDKRL EWVATISSGGSYTYYPDSVKGRFTISRDNAKNTLYLQMSSLKSEDT AMYYCARDGNYQEDYFDYWGQGTTLTVSS Bright-1.3H 38 EVQLVESGGGLVQPGGSRKLSCAASGFTFSSFGMHWVRQAPEKGL EWVAYISSGSRTIYYADSVKGRFTISRDNPKNTLFLQMTSLRSEDTA IYYCAREGYAYDVDYWGQGTTLTVSS Bright-1.4H 39 EVQGVESGGGLVQPGGSRKLSCAASGFTFSSFGMHWVRQAPEKGL EWVAYISSGSSNIFYSDTVKGRFTISRDNPKNTLFLQMTSLRSEDTA MYYCARYDYGKDFDYWGQGTTLTVSS

Example 6 Proteomic Quantization of V Genes in IgG of Serum

Serum Ig proteins were isolated by affinity chromatography using protein A or G chromatography with elution using acetate buffer, pH 3.0 (or anti-IgA and anti-IgM antibodies for affinity purification of the other major Ig classes). Additionally, antigen-specific IgGs were further purified by affinity chromatography on an immobilized antigen column and elution with either 6 M urea or acetate buffer pH 3.0. Eluted samples were dialyzed in PBS for further processing.

Purified IgG proteins or FAB fragments as appropriate were denatured in 50% 2,2,2-trifluoroethanol (TFE). 15 mM dithiothreitol was added to reduce proteins, and samples were incubated at 55° C. for 45 min., followed by alkylation with 55 mM iodoacetamide for 30 min. at room temperature. Samples were diluted 10-fold to 5% TFE concentration and subjected to protease digestion by appropriate proteases that preserve the CDR3 domains largely intact. The selection of the proper proteases is based on the bionformatic analysis of the V domain protein sequences so that protease cleavage generates peptides that cleave N- and C-terminal of the CDR3, leaving the CDR3 sequence largely intact in most sequences on the data base. In one embodiment proteolytic cleavage was accomplished using sequencing grade trypsin (Sigma) at 37° C. for 4 hr. In a separate embodiment a combination of the GluC (NEB) and LysC (Sigma) proteases were used to generate a distinct set of proteolytic peptides that in computational tests provide better coverage of the CDR3. In yet a third embodiment, proteolytic cleavage was accomplished using engineered variants of trypsin or of the bacterial outer membrane protease OmpT selected again so that cleavage preserves the integrity of CDR3. Digestions were quenched with 1% formic acid. Sample volume was reduced by speedvac centrifugation. To remove contaminants, peptides were bound and washed on C-18 Hypersep SpinTips (Thermo Scientific) and filtered through 10 kDa Microcon YM-10 centrifugal filters (Amicon) prior to LC-MS/MS analysis.

In certain embodiments, CDR3 peptides were enriched by affinity purification of Cys containing immunoglobulin peptides. An invariant Cys residue is localized at the N-terminus of the CDR3 domain. VL-Cκ, λ and VH-CH1 polypeptides in FAB proteins each contain 4 Cys. Thus, isolation of Cys containing peptides from either the heavy or light chain results in significant enrichment of CDR3 peptides to approximately 25% of the pool. Enrichment of Cys containing peptides therefore significantly reduces the number of redundant peptides interrogated by MS and increases the depth of coverage. For purification of Cys-containing CDR3 peptides, the peptide fragments generated above are reacted with a 3-fold molar excess of thiol specific biotinylation reagents such as isodoacetyl-LC-biotin (ProtecoChem) according to the manufacturers instructions. Following biotinylation, Cys-containing peptide fragments are separated by affinity chromatography on neutravidin and elution with a large excess (5 mM) free biotin.

Peptides are then separated on a reverse phase Zorbax C-18 column (Agilent) running a 230 min elution gradient from 5% to 38% acetonitrile, 0.1% formic acid. Peptides are eluted directly into an LTQ-Orbitrap mass spectrometer (Thermo Scientific) by nano-electrospray ionization. Data-dependant ion selection was enabled, with parent ion mass spectra (MS1) collected at 100K resolution. Ions with known charge >+1 were selected for CID fragmentation spectral analysis (MS2) in order of decreasing intensity, with a maximum of 12 parent ions selected per MS1 cycle. Dynamic exclusion was activated, with ions selected for MS2 twice within 30 sec. excluded from MS2 selection for 30 sec.

Ions identified in an LC-MS/MS run as corresponding to peptides from the constant regions of the heavy and light chains are excluded from data-dependant selection in subsequent experiments in order to increase selection of peptides from the variable region. As an alternate method, predicted protease-specific peptides overlapping the hyper-variable regions of heavy and light chains are compiled into an inclusion list for which corresponding parent ions are preferentially selected for MS2 fragmentation analysis.

Sample-specific protein sequence databases are created from the high-throughput V gene cDNA sequencing data. LC-MS/MS data are searched against this database using the Sequest search algorithm as part of the Bioworks software package (Thermo Scientific). Filters are applied to ensure high confidence peptide identifications as follows: ΔCN ≧0.250; XCorr=2.0, 2.5, and 3.0 for +2, +3, and ≧+4 charge; and accuracy ≦10.0 ppm. Alternatively, other label-free (Silva et al., 2006b; Gygi et al., 1999; Ross et al., 2004) or isotope label-based quantitative methods for mass spectrometry can be used to determine the abundancy of specific CDR3 families at the protein level.

It should be noted that for plasma cell transcript abundancy and protein levels based on CDR3 peptide counting are often not correlated. There are three reasons for this discrepancy. First and foremost, the V gene abundancy profile provides a snapshot of antibody transcription and protein synthesis. However, antibodies persist in circulation with a t_(1/2) of approx 14 days for IgGs. The plasma cell population is dynamic and is renewed continuously. Thus well transcribed Ig that are not as highly abundant in the serum may be the product of new plasma cells that have only recently populated the plasma compartment. The presence of “declining” plasma cells that show low transcription rates but are highly represented supports this hypothesis (shown in red and underlined in Table 7). Second, the sequencing data comprised all V genes irrespective of isotype where the proteomic data reflects only the IgG pool. Therefore, some CDR3 not represented or poorly represented may correspond to IgA and would not be detected by the present analysis. Third, because trypsinization was used for fragmentation, some CDR3s may have been partially cleaved and hence underrepresented as intact peptides (CDR3 sequences containing putative trypsin cleavage sites are highlighted in gray in Table 7).

In Table 7, Frequency of VL transcripts in bone marrow plasma cells (CD138⁺, CD45R(B220)⁻/CD49b⁻) isolated by MACS/FACS and analyzed by Roche 454 sequencing (aprx 15-35K complete reads). The CDR3 peptide counts determined by shotgun proteomic analysis of the purified IgG from the serum from the same mouse are also shown. CDR3 sequences containing putative proteolytic sites and therefore underrepresented during fragmentation are shown. CDR3 peptides that show relatively high counts but low transcript levels are in red and underlined.

TABLE 7 Example of CDR3 VL gene mRNA sequence abundancy in plasma cells and the corresponding relative abundancy of the respective antibodies in serum as determined by counting the CDR3 peptide identified by MS. mRNA CDR3 VL CDR3 SEQ ID sequence Peptide sequence NO: Count Count CFQGSHVPLTF 40 2404 261 CWQGTHFPHF 41 296 9 CWQGTHFPTF 42 284 10 CWQGIHFPTF 43 219 3 CLQGSHVPLTF 44 196 38 CWQGTHFPQTF 45 188 9 CSQSTHVPWTF 46 159 10 CFQGSHVPWTF 47 109 6 CFQGSHVPRTF 48 151 14 CWQGTHFPRTF 49 145 13 CFQGSHFPYTF 50 143 14 CFQGSHVPYTF 51 95 19 CSQSTHVPYTF 52 92 4 CQQSNEDPRTF 53 47 2 CQQSKEVPWTF 54 46 2 CQHHYGIPRTF 55 43 35 CSQSTHVPFTF 56 39 8 CQHSRELPFTF 57 28 52 CFQGSHVPFTF 58 19 9 CQQSRKVPWTF 59 14 10

In some embodiments, grouping of V genes based on CDR3 families substantially improves quantitation of the peptide dataset. This introduced a number of additional steps into the bioinformatics analysis pipeline: (1) After performing the shotgun proteomics experiments and identifying peptides based on the standard mass spectrometry analysis pipeline and the sample-specific sequence database, peptides that overlap CDR3 regions are identified. (2) These observed peptides are mapped to V gene cDNA-defined CDR3 families, and (3) Spectral counts attributable to each CDR3 family are defined. A comparison of the rank-order abundancy of the CDR3 peptides identified by the MS proteomic analysis with the DNA sequence analysis is shown in Table 7. Comparison of the VL transcript abundancy with protein abundancy as determined from the CDR3 analysis indicates that the most highly represented antibody (expressed at 17% of all the VL transcripts in the bone marrow plasma cell population!) is also most highly represented among the CDR3 peptides.

In several cases, plasma cell transcription does not correlate with the concentration of antibodies in serum. This finding has many important implications for disease detection and therapeutic antibody discovery and is related to three factors: First, transcript analysis provides only a snapshot of transcription and protein synthesis. However, antibodies persist in circulation with a t_(1/2) of approx 14 days for IgGs. The plasma cell population is dynamic and is renewed continuously. Thus well transcribed Ig that are not as highly abundant in the serum may be the product of new plasma cells that have only recently populated the plasma compartment. The presence of “declining” plasma cells that show low transcription rates but are highly represented supports this hypothesis. Second, the sequencing data comprised all V genes irrespective of isotype where the proteomic data reflects only the IgG pool. Therefore, some CDR3 not represented or poorly represented may correspond to IgA and would not be detected by the present analysis. Third, the proteolytic fragmentation used to generate this data led to some CDR3s that were partially cleaved and hence underrepresented as intact peptides (CDR3 sequences containing putative trypsin cleavage sites are highlighted in green). As discussed above this issue is successfully dealt with by judicious selection of fragmentation conditions.

Example 7 Construction of Synthetic Antibody Genes

The most abundant VL and VH protein sequences identified by the proteomic analysis and those from the gene sequencing analyses are then synthesized by automated gene construction adapting a previously developed process that exploits sequence data basing software and liquid handling robots for the rapid and efficient production of high-fidelity synthetic genes (Cox et al., 2007). Briefly, gene fragments are generated from synthetic oligonucleotides using inside-out nucleation PCR reactions, subsequent stitch-overlap extension PCR reactions are used and thus obviated the need for purification steps, making the process amenable for automation. Fragment design and relevant overlaps were automated through software, which further generated oligonucleotide synthesizer worklists and robot operation scripts for construction and assembly.

For IgG production the VH and VL genes are paired based on the data from the proteomic and gene sequence frequency distributions. VH and VL genes occurring at the similar frequencies are paired. The inventors find that this strategy results in a high rate of success (>75%) of correctly paired antibodies exhibiting high antigen affinity (Tables 8). In Table 8, VL and VH have CDR3 sequences paired based on abundancy rank order shown in Table 2 and affinities of the respective antibodies were measured by ELISA.

TABLE 8 Examples of synthetic antibodies identified in serum via the technology disclosed herein and their antigen binding affinities. VL-VH pair/ IC₅₀ by Antigen CDRL3 CDRH3 ELISA C1s 2.1L-2.1H FQGSHVPLT SDRYDGYFDY   50 nM (SEQ ID NO: 60) (SEQ ID NO: 19) 2.3L-2.2H WQGTHFPH WLLLAY (SEQ    0.43 nM (SEQ ID NO: 61) ID NO: 21) 2.3L-2.3H WQGTHFPH SDGYYYFDY  100 nM (SEQ ID NO: 61) (SEQ ID NO: 23) BRIGHT 1.1L-1.1H LQYASSPFT HDYGNYVDY ~100 (ND) (SEQ ID NO: 63) (SEQ ID NO: 10) 1.2L-1.4H WQGTHFPRT YDYGKDFDY NA (SEQ ID NO: 64) (SEQ ID NO: 16) 1.4L-1.4H QQRSSYPLT YDYGKDFDY  ~10 (ND) (SEQ ID NO: 65) (SEQ ID NO: 16) 1.2L-1.1H WQGTHFPRT HDYGNYVDY    1μM (SEQ ID NO: 64) (SEQ ID NO: 10)

Example 8 IgG Expression and Binding Analysis

Synthetic VL and VH genes are assembled for full-length IgG expression. Synthetic gene products are purified by gel extraction following digestion with the restriction enzymes BssHII/BsiWI and BssHII/NheI for VL and VH, respectively. Digested VL and VH genes are ligated into the vectors pMAZ-IgL and pMAZ-IgH1, respectively. pMAZ-IgL carries the constant human kappa light chain antibody region and pMAZ-IgH carries the constant human heavy chain antibody region of IgG1. Vectors are transformed into E. coli Jude 1 cells and plated on Luria Broth (LB, Miller) agar plates supplemented with 100 ug/ml ampicillin. Single colonies are selected and verified for correct V gene sequence. E. coli cells carrying pMAZ-IgL and pMAZ-IgH vectors are then grown in 10 ml TB supplemented with 100 ug/ml ampicillin isolated and DNA is purified. 20 μg each of purified pMAZ-IgL and pMAZ-IgH are used for co-transfection and transient expression from HEK293-F cells following the Freestyle MAX expression system protocol (Invitrogen). HEK293-F cells are grown for 96 h following transfection and media was harvested and IgG is purified by a protein-A agarose chromatography column.

To determine antigen affinity, a standard ELISA is performed with a 96 well plate coated with either purified antigen at 2 ug/ml in PBS and blocked with 0.5% BSA. Purified IgGs were added to the plate at various concentrations for 1.5 h and washed with PBS/0.05% Tween-20. A polyclonal antibody of goat anti-human Fc region conjugated HRP was used for detection and developed with TMB substrate and stopped with 2N H₂SO₄. The absorbance was measured at 450 nm with a 96 well spectrophotometer. A titration curve of purified IgGs was used to determine an approximate IC50 for binding (Table 8).

Alternatively, a whole cell ELISA can be performed to estimate binding affinity. Tumor cells at 2×10⁵ cells/ml are added to a 96 well cell culture cluster plate in 100 ul of PBS. Cells were then exposed to purified IgGs at various concentrations for 1.5. The plate was then centrifuged at 2000 RPM for 1 min to pellet cells and resuspended and washed with PBS and repeated 3 times. For detection, a polyclonal antibody of goat anti-human Fc region conjugated HRP was and developed with TMB substrate and stopped with 2N H₂SO₄. The absorbance was measured at 450 nm with a 96 well spectrophotometer.

Example 9 Isolation of Monoclonal Antibodies by Mining the Variable Gene Repertoire of Plasma Cells

A simple and rapid method has been developed for antibody isolation without the need for any laborious screening steps. High-throughput DNA sequencing was exploited to analyze the V_(L) and V_(H) antibody gene repertoires derived from the mRNA transcripts of fully differentiated mature B cells—antibody secreting plasma cells—found within the bone marrow of immunized mice. Following bioinformatic analysis, several abundant antibody V_(L) and V_(H) gene sequences could be identified within the repertoire of each immunized mouse. V_(L) and V_(H) genes were paired according to their relative frequencies within the repertoire. Antibody genes were rapidly synthesized by oligonucleotide and PCR assembly by utilizing automated liquid handling robots. Antibodies were recombinantly expressed in bacterial and mammalian systems as single-chain variable fragments (scFv) and full-length IgG, respectively (FIG. 2). Finally, it was confirmed that the resulting antibodies were overwhelmingly antigen-specific (21/27 or 78%), thus providing a method for rapid and direct isolation of MAbs without screening.

B cell maturation culminates in the terminal, non-proliferative stage of B cell development—the formation of plasma cells that serve as immunoglobulin production factories. Plasma cells represent less than 1% of all lymphoid cells and yet are responsible for the overwhelming majority of antibodies in circulation (Manz et al., 2005; Shapiro-Shelef and Calame, 2005). The bone marrow constitutes the major compartment where plasma cells take residency and produce antibodies for prolonged periods of time. In mice, a stable and highly-enriched antigen-specific BM-PC population of ˜10⁵ cells (10-20% of all BM-PCs) appears 6 days following secondary immunization and persists for prolonged periods (Manz et al., 1997). In contrast, the splenic plasma cell population is highly transient, as it peaks at day 6 and rapidly declines to <10⁴ cells by day 11. Importantly, BM-PCs are responsible for the synthesis of the most abundant circulating antibodies, which in turn are likely to play a dominant role in pathogen neutralization and other protective humoral immune responses (Manz et al., 2005).

To examine the dynamics of the antibody V gene repertoires in BM-PCs, especially early after challenge (i.e., to mimic situations where mice exhibit weak immune responses), pairs of mice were immunized with chicken egg ovalbumin (OVA), human complement serine protease (C1s), human B cell regulator of IgH transcription (Bright), or adjuvant only. Antigen was co-injected with complete Freund's adjuvant followed by a secondary booster immunization in incomplete Freund's adjuvant. Mice were sacrificed 6 days post-secondary immunization and BM-PCs (CD45R⁻CD138⁺) were isolated to high purity (FIG. 3). Total RNA was extracted and reverse transcribed for synthesis of first strand cDNA. Well characterized (Mazor et al., 2007), degenerate V gene primer mixes were utilized for second strand amplifications, resulting in V_(L) and V_(H) PCR products of high purity (FIG. 4), which were then submitted for high-throughput DNA sequencing of long reads using 454-GS FLX technology (Roche).

Unlike recent high-throughput sequencing analyses that explored V gene repertoire diversity in zebrafish (Weinstein et al., 2009), humans (Boyd et al., 2009; Glanville et al., 2009), or synthetic libraries (Ge et al., 2010), the goals were to: (1) identify highly expressed V genes likely to be antigen-specific and (2) to determine the relative V gene transcript abundance in the BM-PC repertoires of immunized mice. These tasks do not require exhaustive coverage of the V gene repertoire; it has been found that obtaining >5K V gene sequences per BM-PC sample is sufficient to provide the information needed for antibody discovery, minimizing DNA sequencing costs.

454 reads were first processed by multiple sequence and signal filters, and then subjected to a simple and rapid bioinformatic analysis that relied on homologies to conserved framework regions within V genes in order to identify the most common complementarity determining region 3 (CDR3) sequences (FIG. 5).

This approach correctly identified ˜94% of V_(H) and ˜92% of V_(L) sequences in the Kabat database (Table 3). Out of a total of 415,018 reads, 23.2% contained CDR3 of V_(H) (CDRH3) and 26.6% contained CDR3 of V_(L) (CDRL3) sequences (Table 9), representing 6,681-16,743 and 7,112-21,241 CDRH3 and CDRL3 sequences reads per mouse, respectively.

TABLE 9 Number of CDR3 containing sequences identified from 454 GS-FLX DNA sequencing using CDR3 flanking consensus motifs. Sequences Containing Sequences Containing CDR-H3 motif CDR-L3 motif Number Number 454 GS- Number of CDR- Number of CDR- FLX of H3 as of L3 as Sequencing Total Unique Single Total Unique Single Sample Size Number CDR-H3 Copy Number CDR-L3 Copy Adjuvant-1 32066 6681 2706 1811 7112 1638 1053 Adjuvant-2 86720 16743 4640 2890 21241 3136 1888 Ova-1 63872 15350 4789 3010 13355 2251 1355 Ova-2 72257 15751 3821 2401 17200 2786 1700 C1s-1 43753 11595 2440 1443 13972 1706 1045 C1s-2 39961 9071 1799 999 14664 1477 847 Bright-1 36599 9453 2025 1178 12209 1383 632 Bright-2 39790 11769 2530 1210 10441 1422 578 Total 415018 96413 24750 14942 110194 15799 9098 Unique Sequences Across All 21271 8690 Samples

For each mouse, frequency distributions of the CDR3s were calculated. Sequencing of the same samples, from separate cDNA library preparations by different facilities gave quantitatively similar rankings of CDR3. As shown in Table 10 the same rank order frequencies are observed for all the highly expressed CDR3s. This is important because as discussed below our approach for antibody discovery exploits the rank-order frequency of V genes and specifically on the identification of the most highly expressed clones. V gene sequences containing a particular CDR3 were accepted as full-length if they covered all 3 CDRs. Pairwise identities and frequencies were calculated by multiple sequence alignments followed by germline analysis (FIG. 5 and bioinfomatic methods described below). A graphical user interface application was developed to enhance data analysis and visualization of the results (FIG. 6).

TABLE 10 Comparison of 454 DNA sequencing results generated by two different facilities from two different cDNA library preparations (SeqWright and UT-Austin Genome Sequencing Center). Sample Adjuvant-1 OVA-2 Facility SeqWright UT-Austin SeqWright UT-Austin Total seq reads SEQ ID 7112 20850 17200 17291 CDR-L3 seq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

Analysis of the BM-PC repertoires led to several interesting observations. First, ˜10-20% of the total repertoire of all immunized mice were on average comprised of only 4 CDRH3 sequences (Table 11). For example, in the two mice immunized with C1s, the frequencies of the most abundant CDRH3s were 7.93% and 10.99% of the total repertoire. Second, as expected for early responses, the most highly abundant CDR3s were assembled from a diverse array of germline V gene segments, with an average somatic mutation rate of only 2 and 5 amino acid substitutions for V_(L) and V_(H), respectively (Tables 12-13). Not surprisingly, certain germline V gene families were represented preferentially in mice responding to particular antigens. For example in mice immunized with C1s, between 15-30% of the entire V_(H) gene repertoire utilized IGHV1 family whereas the adjuvant only immunized mice were dominated by IGHV5 or IGHV6 families (FIG. 7).

TABLE 11 Frequencies (%) of the most highly represented CDRL3 and CDRH3^(a) sequences. Clone Percent CDRL3 Clone Percent CDRH3 Ovalbumin Ovalbumin 1.1L 11.69 WQGTHFPLT 1.1H 7.17 TYGSSYYAMDY SEQ ID 114 SEQ ID 137 1.2L 4.44 OQYNSYPLT 1.2H 1.13 TRLLWLYAMDY SEQ ID 115 SEQ ID 138 1.3L 3.38 QQSNSWYT 1.3H 0.57 DVYDGYAMDY SEQ ID 117 SEQ ID 139 1.4L 2.20 QHHYGTPPWT 1.4H 0.54 NPYAMDY SEQ ID SEQ ID 119 140 2.1L 5.32 WQGTHFPLT 2.1H 7.59 RTTVSRDWYFDV SEQ ID 114 SEQ ID 141 2.2L 4.05 OQYNSYPLT 2.2H 3.22 YYYGSSAMDY SEQ ID 115 SEQ ID 142 2.3L 3.46 QQYSSYPLT 2.3II 2.22 DGWYYFDY SEQ SEQ ID 116 ID 143 2.4L 2.01 QQHYSTPWT 2.4H 2.11 EDDYDLFAY SEQ SEQ ID 120 ID 144 2.5L 1.87 HQWSSYPT 2.5H 1.25 DTTVVEGDYFDY SEQ ID 121 SEQ ID 183 C1s C1s 1.1L 12.95 WQGTHFPQT 1.1H 7.93 GNYYYAMDY SEQ ID 123 SEQ ID 145 1.2L 6.94 QQWSSYPQLT 1.2H 2.64 DMISYWYFDV SEQ ID 129 SEQ ID 146 1.3L 3.81 QNDHSYPLT 1.3H 1.67 EDYGNYWYFDV SEQ ID 130 SEQ ID 147 1.4L 3.16 QQGQSYPFT 1.4H 1.17 EGYYYGSSYFDY SEQ ID 131 SEQ ID 148 2.1L 17.10 FQGSHVPLT 2.1H-A 10.99 SDRYDGYFDY SEQ ID 60 SEQ ID 19 2.2L 2.62 QQSNEDPWT 2.1H-B 9.93 SDRFDGYFDY SEQ ID 132 SEQ ID 20 2.3L 2.20 WQGTHFPH 2.2H 3.30 WLLLAY SEQ ID SEQ ID 61 21 2.4L 1.64 QQHYSTPFT 2.3H 1.65 SDGYYYFDY SEQ SEQ ID 133 ID 23 Bright Bright 1.1L 6.63 LQYASSPFT 1.1H 7.19 IIDYGNYVDY SEQ ID 63 SEQ ID 10 1.2L 4.73 WQGTHFPRT 1.2H 5.62 DGNYQEDYFDY SEQ ID 64 SEQ ID 11 1.3L 4.51 QQNNEDPRT 1.3H 1.91 EGYAYDVDY SEQ SEQ ID 134 ID 12 1.4L 3.59 QQRSSYPLT 1.4H 1.21 YDYGKDFDY SEQ SEQ ID 65 ID 16 2.1L 7.25 WQGTHFPQT 2.1H 2.56 RGDGNYFFDY SEQ ID 123 SEQ ID 149 2.2L 4.51 QQGQSYPWT 2.2H 2.27 GDEAWFAY SEQ SEQ ID 126 ID 150 2.3L 3.12 LQYASSPYT 2.3H 2.04 EGDFDY SEQ ID SEQ ID 135 151 2.4L 2.59 FQGSHVPWT 2.4H 1.63  GGNYDYAMDY SEQ ID 136 SEQ ID 152 ^(a)CDRH3 sequences present at high frequency in both immunized mice and adjuvant only mice were considered background and thus excluded from the list.

TABLE 12 Germline identity and the number of amino acid somatic mutations (SM) of the most highly represented V_(L) and V_(H) ^(a) genes. # SM # SM Clone Germline V_(L) V_(L) Clone Germline V_(H) V_(H) Ovalbumin Ovalbumin 1.1 L V1-135*01 − 2 1.1 V1-5*01 − 5 J5*01 J4*01 − D1-1*01 1.2 L V6-23*01 − 4 1.2 V6-6*02 − 2 J5*01 J4*01 − D2-2*01 1.3 L N/A—low N/A 1.3 V1S132*01 − 14  alignment score J4*01 − D2-3*01 1.4 L V12-44*01 − 1 1.4 V5-6*01 − 7 J1*01 J4*01 − D6-1*01 2.1 L V1-135*01 − 2 2.1 V5-17*02 − 5 J5*01 J1*01 − D2-1*01 2.2 L V6-15*01 − 1 2.2 N/A—low N/A J5*01 alignment score 2.3 L N/A—low 3 2.3 V5-17*02 − 5 alignment score J2*01 − D2-3*01 2.4 L V6-23*01 − 2 2.4 V1-67*01 − 8 J5*01 J3*01 − D2-4*01 2.5 V3-2*02 − 3 J2*01 − D1-1*01 C1s C1s 1.1 L V1-135*01 − 2 1.1 V1-5*01 − 2 J1*01 J4*01 − D2-1*01 1.2 L V4-55*01 − 3 1.2 V7-3*02 − 0 J5*01 J1*01 − D2-4*01 1.3 L V8-28*01 − 1 1.3 V2-9*02 − 3 J5*01 J1*02 − D2-1*01 1.4 L V15-103*01 − 2 1.4 V1-14*01 − 4 J1*01 J2*01 − D1-1*01 2.1 L V1-117*01 − 4 2.1 (A, B) V1-4*01 − 3 J5*01 J2*01 − D2-14*01 2.2 L V3-5*01 − 1 2.2 V5-9-1*01 − 8 J1*01 J3*01 − D2-3*01 2.3 L V1-135*01 − 4 2.3 V1-5*01 − 3 J2*01 J2*01 − D2-3*01 2.4 L V6-25*01 − 0 2.4 V1-7*01 − 5 J4*01 J2*01 − D2-4*01 Bright Bright 1.1 L V9-120*01 − 1 1.1 V5-6*01 − 1 J4*01 J2*01 − D2-1*01 1.2 L V1-135*01 − 3 1.2 V5-6*01 − 2 J1*01 J2*01 − D2-1*01 1.3 L V3-10*01 − 2 1.3 V5-17*02 − 5 J1*01 J2*01 − D1-3*01 1.4 L V4-57*01 − 3 1.4 V5-17*02 − 6 J1*01 J2*01 − D1-1*01 2.1 L V1-135*01 − 3 2.1 V5-6*01 − 3 J1*01 J2*01 − D2-1*01 2.2 L V15-103*01 − 2 2.2 V5-6*01 − 4 J1*01 J3*01 − D4-1*01 2.3 L V9-120*01 − 1 2.3 V5-6-4*01 − 4 J2*01 J2*01 − D3-2*02 2.4 L V1-117*01 − 0 2.4 V14-3*02 − 9 J1*01 J4*01 − D1-1*02 ^(a)V_(H) sequences present at high frequency in both immunized mice and adjuvant only mice were considered background and thus excluded from the list.

TABLE 13 Average somatic mutations in nucleotides (nt) and amino acids (AA) of the top 30 V_(H) sequences in each BM-PC repertoire. Mouse # of nt # of AA Adjuvant-1 5.3 2.9 Adjuvant-2 5.2 2.7 OVA-1 5.5 3.3 OVA-2 7.0 3.8 C1s-1 5.0 2.6 C1s-2 6.7 3.9 Bright-1 4.9 2.8 Bright-2 7.5 4.6

In most instances the V genes encoding a highly abundant CDR3 were dominated by one sequence with the second most abundant V gene sequence (somatic variant) being present at >10-fold lower level and differing from the dominant sequence by 1-2 amino acids.

The following test and tables provide further information regarding the antibody repertoires that were studied using the techniques detailed herein. There were some instances in which abundant CDRH3s were encoded by several V genes that were represented at comparable frequencies (FIGS. 8A-8C and Table 14). Notably, the V_(H) repertoires were quite distinct even among genetically identical littermates immunized with the same antigen on the same day. For mice immunized with C1s or Bright, each mouse developed a distinct and diverse set of abundant CDRH3 sequences (FIG. 9 and Table 15). This suggests that each mouse generates its own unique and highly expressed V_(H) gene repertoire, which may allow for the discovery of a panel of diverse antibodies. One exception however was that in the cohort of OVA-immunized mice we observed that a few abundant CDRH3 sequences were also present at high frequency in other mice, suggesting that the corresponding antibodies may be poly-specific. Not surprisingly, some moderately represented CDRH3 sequences from animals that received adjuvant only, were also present in immunized mice (FIG. 9). Antibodies encoding these sequences were probably specific to adjuvant or to common natural antigens. CDRL3 diversity was lower with several promiscuous sequences represented at high frequency in several mice (Table 16). Fourth, even though the BM-PC V_(H) repertoires were largely comprised of sequences unique to each mouse, principal component analysis of CDRH3s shared between mice revealed distinct clustering of the data for each cohort (i.e., same cage and litter) immunized at the same time but with different antigens (FIG. 10). This signature likely reflects environmental factors, such as the antigenic history of the animal groups, and suggests that V gene repertoire analysis may provide valuable diagnostic information.

TABLE 14 The most highly represented CDR3 groups and their full-length variable heavy (V_(H)) and variable light (V_(L)) gene frequencies and homologies. SEQ ID CDR3 1st V_(H) Freq 2nd V_(H) Freq V_(H) Antigen CDR3 NO: Freq (%) (%)^(a) (%)^(a) Homology^(b) OVA-1.1 GSSYYAMDY 153 7.11 60.0 1.7 96.1 OVA-1.2 DYYGSSYWYFDV 154 1.10 47.1 5.8 89.9 OVA-1.3 DNWDWYFDV 14 0.57 49.0 4.0 95.0 OVA-1.4 LLWLYAMDY 155 0.54 54.7 4.7 97.3 OVA-2.1 RTTVSRDWYFDV 141 7.61 15.3 5.6 92.3 OVA-2.2 YYYGSSAMDY 142 3.23 26.0 10.8 96.0 OVA-2.3 DGWYYFDY 143 2.22 22.7 4.1 89.1 OVA-2.4 EDDYDLFAY 144 2.10 9.4 8.7 94.9 C1s-1.1 GNYYYAMDY 145 7.93 68.8 1.1 97.9 C1s-1.2 DDGYWYFDV 156 5.14 60.9 5.3 90.0 C1s-1.3 YYYGSSAMDY 142 4.37 58.5 3.7 94.5 C1s-1.4 DMISYWYFDV 146 2.64 70.9 1.1 90.0 C1s-2.1 SDRYDGYFDY 19 10.99 11.1 9.4 95.7 C1s-2.2 SDRFDGYFDY 20 9.93 12.5 4.2 94.7 C1s-2.3 WLLLAY 21 3.30 26.3 7.7 88.8 C1s-2.4 YGNYFDY 22 2.47 72.1 1.4 96.8 Bright- HDYGNYVDY 10 7.20 66.2 2.6 98.7 1.1 Bright- DGNYQEDYFDY 11 5.62 63.1 5.9 98.6 1.2 Bright- EGYAYDVDY 12 1.91 27.4 23.9 95.6 1.3 Bright- DDYDWYFDV 13 1.54 59.3 2.8 97.5 1.4 Bright- RGDGNYFFDY 149 2.57 16.1 14.0 95.0 2.1 Bright- GDEAWFAY 150 2.27 43.3 6.7 97.1 2.2 Bright- EGDFDY 151 2.03 14.9 8.1 95.3 2.3 Bright- YYYGSSYFDV 157 1.84 77.8 0.7 99.2 2.4 CDR3 1st V_(L) Freq 2nd V_(L) Freq V_(L) Antigen CDRL3 Freq (%) (%)^(a) (%)^(a) Homology^(b) OVA-1.1 WQGTHFPLT 114 11.70 41.4 1.8 92.1 OVA-1.2 QQSNSWYT 117 4.40 54.5 2.4 94.0 OVA-1.3 QQYSSYPLT 116 3.38 46.2 1.9 93.9 OVA-1.4 QHHYGTPPWT 119 2.20 49.7 2.1 93.7 OVA-2.1 WQGTHFPLT 114 5.32 33.3 2.3 93.7 OVA-2.2 QQYSSYPLT 116 4.05 43.6 1.1 94.3 OVA-2.3 QQYNSYPLT 115 3.46 20.1 4.5 92.3 OVA-2.4 QQHYSTPWT 120 2.01 50.2 2.6 95.3 C1s-1.1 WQGTHFPQT 123 12.95 68.8 1.1 97.9 C1s-1.2 QQWSSYPQLT 129 6.94 60.9 5.3 90.0 C1s-1.3 QNDHSYPLT 130 3.81 58.5 3.7 94.5 C1s-1.4 QQGQSYPWT 126 3.16 70.8 1.1 98.5 C1s-2.1 FQGSHVPLT 60 17.10 5.7 4.7 90.4 C1s-2.2 QQSNEDPWT 132 2.62 65.7 2.8 97.4 C1s-2.3 WQGTHFPH 61 2.20 36.1 18.5 96.5 C1s-2.4 WQGTHFPT 158 2.15 39.2 15.6 96.9 Bright- LQYASSPFT 63 6.64 74.0 1.0 98.3 1.1 Bright- WQGTHFPRT 64 4.73 60.8 1.5 97.9 1.2 Bright- QQNNEDPRT 134 4.51 61.8 3.7 97.8 1.3 Bright- QQRSSYPLT 65 3.59 68.4 0.8 96.5 1.4 Bright- WQGTHFPQT 123 7.24 44.5 5.7 95.8 2.1 Bright- QQGQSYPWT 126 4.50 71.3 1.0 98.8 2.2 Bright- LQYASSPYT 135 3.12 70.7 2.0 98.6 2.3 Bright- FQGSHVPWT 136 2.58 47.3 3.8 95.0 2.4 ^(a)The frequencies of the top two V_(H) and V_(L) full-length sequences of a particular CDR3 group. ^(b)The V_(H) and V_(L) homologies were determined by calculating the pairwise identity by multiple sequence alignment of all V genes that shared the same CDR3.

TABLE 15 Occurrence of the highest frequency CDRH3s from the bone marrow plasma cell repertoire of mice immunized with C1s, and their relative frequency in mice immunized with adjuvant or different antigens. C1s - C1s - Adjuv- Adjuv- Antigen 1 2 Br-1 Br-2 OVA-1 OVA-2 1 2 Total Seq Reads 11,595 9,071 9,453 11,769 15,350 15,751 6,681 16,743 CDRH3 % % % % % % % % GNYYYAMDY 7.93 0.01 0.01 0.01 0.00 0.00 0.04 0.01 SEQ ID NO: 145 DDGYWYFDV 3.00 0.00 0.12 0.00 0.01 0.16 0.00 0.28 SEQ ID NO: 156 YYYGS SAMDY 2.68 0.15 0.24 0.29 0.00 3.22 0.00 0.00 SEQ ID NO: 142 DMISYWYFDV 2.64 0.00 0.00 0.00 0.00 0.00 0.00 0.00 SEQ ID NO: 146 DGYDWYFDV 2.26 0.06 0.00 0.05 0.02 0.46 0.00 0.07 SEQ ID NO: 159 DDYDWYFDV 1.97 0.03 1.53 0.01 0.02 0.10 0.09 2.11 SEQ ID NO: 13 GSSYYAMDY 1.67 0.00 0.00 0.00 0.00 0.00 0.00 0.00 SEQ ID NO: 153 EDYGNYWYFDV 1.67 0.21 0.41 0.40 7.17 0.53 0.00 0.01 SEQ ID NO: 147 QGYDYDPYAMDY 1.22 0.00 0.00 0.00 0.00 0.00 0.75 0.00 SEQ ID NO: 160 EGYYYGS SYFDY 1.17 0.00 0.00 0.00 0.00 0.00 0.00 0.00 SEQ ID NO: 148 TGFDY 1.11 0.00 0.00 0.02 0.01 0.01 0.00 0.01 SEQ ID NO: 161 KGSTTATYFDY 1.06 0.00 0.00 0.00 0.00 0.00 0.00 0.00 SEQ ID NO: 162 SDRYDGYFDY 0.09 10.99 0.04 0.01 0.00 0.00 0.00 0.00 SEQ ID NO: 19 SDRFDGYFDY 0.05 9.93 0.05 0.03 0.00 0.00 0.00 0.00 SEQ ID NO: 20 WLLLAY 0.00 3.30 0.01 0.02 0.00 0.00 0.00 0.00 SEQ ID NO: 21 YGNYFDY 0.02 2.39 0.01 0.01 0.00 0.02 0.00 0.02 SEQ ID NO: 22 SDGYYYFDY 0.02 1.65 0.00 0.00 0.00 0.00 0.00 0.00 SEQ ID NO: 23 SGGNYDAMDY 0.00 1.17 0.02 0.00 0.00 0.00 0.00 0.00 SEQ ID NO: 24 YYDYDKAYYFDY 0.03 1.15 0.00 0.00 0.00 0.00 0.00 0.00 SEQ ID NO: 25

TABLE 16 Occurrence of the highest frequency CDRL3s from the bone marrow plasma cell repertoire of mice immunized with C1s, and their relative frequency in mice immunized with adjuvant or different antigens. OVA- OVA- Adjuv- Adjuv- Antigen C1s -1 C1s -2 Br-1 Br-2 1 2 1 2 Total Seq Reads 13,972 14,664 12,228 10,452 13,355 17,200 7,112 21,241 CDRL3 % % % % % % % % WQGTHFPQT 12.95 1.56 2.33 7.25 1.66 1.63 1.69 1.54 SEQ ID NO: 123 QQWSSYPQLT 6.94 0.01 0.00 0.00 0.00 0.00 0.00 0.00 SEQ ID NO: 129 QNDHSYPLT 3.81 0.04 0.13 0.04 0.11 0.12 0.18 0.10 SEQ ID NO: 130 QQGQSYPWT 3.16 0.48 3.21 4.50 0.67 1.07 0.65 1.42 SEQ ID NO: 126 FQGSHVPWT 2.76 0.83 1.04 2.59 0.37 0.28 0.44 0.30 SEQ ID NO: 136 QQGQSYPFT 2.64 0.10 0.39 0.12 0.01 0.00 0.00 0.01 SEQ ID NO: 131 LQHGESPFT 2.43 1.55 2.59 2.41 0.00 0.02 0.01 0.01 SEQ ID NO: 163 QQGQSYPLT 2.07 1.05 2.97 0.11 0.25 0.26 0.17 0.58 SEQ ID NO: 164 OQSK£VPPT 1.74 0.53 0.08 0.11 0.07 0.04 0.13 0.07 SEQ ID NO: 165 QQHYSTPWT 1.47 1.41 0.36 0.82 0.88 2.01 1.42 1.13 SEQ ID NO: 120 QNDYSFT 1.46 0.04 0.01 0.05 0.00 0.00 0.00 0.00 SEQ ID NO: 166 WQGTHFPWT 1.17 0.68 1.55 0.99 0.54 0.83 0.93 0.95 SEQ ID NO: 167 WQGTHFPRT 1.12 1.15 4.73 0.94 1.27 1.23 1.18 2.70 SEQ ID NO: 64 FQGSHVPFT 0.97 0.14 0.47 0.47 0.01 0.00 0.00 0.00 SEQ ID NO: 168 WQGTHFPT 0.95 0.04 0.03 0.00 0.00 0.01 0.00 0.00 SEQ ID NO: 158 FQGSHVPLT 0.19 17.10 2.29 0.23 0.16 0.23 0.24 0.19 SEQ ID NO: 60 QQSNEDPWT 0.23 2.62 0.50 1.00 0.28 0.32 0.24 0.23 SEQ ID NO: l32 WQGTHFPH 0.01 2.20 0.00 0.00 0.00 0.00 0.00 0.00 SEQ ID NO: 61 WQGTHFPT 0.00 2.11 0.00 0.07 0.02 0.02 0.04 0.00 SEQ ID NO: 158 QQHYSTPFT 0.19 1.64 0.17 0.15 0.00 0.00 0.00 0.01 SEQ ID NO: 133 WQGTHFPQT 12.95 1.56 2.33 7.25 1.66 1.63 1.69 1.54 SEQ ID NO: 123 LQHGESPFT 2.43 1.55 2.59 2.41 0.00 0.02 0.01 0.01 SEQ ID NO: 163 LQGSHVPLT 0.01 1.50 0.01 0.00 0.01 0.00 0.00 0.00 SEQ ID NO: 169 QQHYSTPWT 1.47 1.41 0.36 0.82 0.88 2.01 1.42 1.13 SEQ ID NO: 120 LQHGESPYT 0.44 1.23 0.84 0.66 0.25 0.44 0.76 0.61 SEQ ID NO: 170 SQSTHVPWT 0.89 1.21 1.68 1.30 0.50 0.51 0.32 0.28 SEQ ID NO: 171 WQGTHFPRT 1.12 1.15 4.73 0.94 1.27 1.23 1.18 2.70 SEQ ID NO: 64

It should be noted that a few copies (typically <5) of the most abundant CDRH3 sequences raised to a given antigen were observed at very low levels (typically <0.1%) in the CDRH3 repertoires of mice receiving other antigens. Since several of the respective V genes were shown to encode antigen-specific antibodies (see below), the inventors believe that the presence of these sequences in mice immunized with other antigens might originate from low levels of cross-sample contamination, a conclusion supported by the biased distributions of common CDRH3 sequences within the same cohort (FIG. 11). Because of the high sensitivity of 454 DNA sequencing, even with the utmost care it is not possible to completely rule out low-level contamination (sequence noise) during library preparation/multiplex sequencing. Although an important consideration for studies aiming to compare unbiased repertoires (Weinstein et al., 2009; Boyd et al., 2009), sequence noise does not impact the methodology described herein, since the most abundant V genes in the BM-PC repertoire are represented at levels 20- to >100-fold higher than the sequence noise level.

Manual screening of small combinatorial libraries of scFvs in E. coli using the entire BM-PC V genes pool (i.e. not of the most abundant V genes as determined by the NextGen sequencing analysis) led to a low yield of antigen-specific clones (<4 positive clones per 96 well plate, data not shown). Upon further analysis, most of these scFvs displayed low apparent affinity by ELISA and/or poor expression and aggregation. The inventors reasoned that this was a consequence of combinatorial pairing: even if a V_(L) and a V_(H) gene are represented at 5% of the cDNA pool, assuming no PCR biases in scFv assembly, the probability of correct pairing is only 0.25%, and therefore discovery of positive clones would require an extensive amount of screening.

To overcome these problems, and to avoid screening altogether, it was contemplated that V_(L) and V_(H) genes represented at approximately the same frequency likely arise from the same plasma cell and hence, are naturally paired. To test this hypothesis, the top 4-5 most abundant full-length V_(L) and V_(H) genes from each mouse (excluding V_(H) sequences that were cross-represented in adjuvant-only mice), which accounted for a minimum of 0.5% of the repertoire, were gene synthesized as pairs, recombinantly expressed, and tested for antigen binding.

Synthetic genes were constructed by robotically assisted, high-throughput DNA synthesis as shown in detail above. Briefly, gene fragments (lengths from 200 to 500 nucleotides) were generated using inside-out nucleation PCR reactions. The design of these fragments and relevant overlaps was automated using customized software to facilitate robotic synthesis and assembly. Alignment and “padding” of the sequences at either end yielded genes of identical length and permitted the use of a generic overlapping assembly strategy that ensured the greatest oligonucleotide re-use (FIG. 12). In this manner, up to 48 V_(L) and 48 V_(H) genes could be synthesized and validated for correct ORF by one researcher within one week, at a reagent cost <$2,000.

In most cases, V_(L) and V_(H) pairing was determined by rank ordering of CDR3 frequency within the repertoire. In cases where two V_(L) or V_(H) genes were found at very similar frequencies, multiple V_(L)-V_(H) combinations were constructed. Paired V genes were then expressed as scFv fragments in E. coli.

E. coli whole cell lysates were prepared to express antibody single chain variable fragments (scFvs) that were constructed by pairing the most abundant V genes (as shown above). VL and VH gene pairing was determined by relative frequency (%) of the respective V genes in the bone marrow plasma cell repertoires. ELISA analysis was performed to determine antigen binding (see Online Methods). (+): >3-fold ELISA signal on antigen-coated wells relative to wells coated with unrelated antigen (bovine serum albumin and/or gelatin).

ELISA analysis of bacterial lysates indicated that the resulting antibodies were overwhelmingly antigen-specific (˜78%): 21/27 antigen specific antibodies were obtained from six mice immunized with three different protein antigens (Table 17). To further evaluate the utility of this simple pairing strategy, there was constructed a combinatorial library of scFvs comprising the 4 most abundant V_(L) and V_(H) genes from each of the two mice immunized with C1s. scFv antibodies were expressed in E. coli; binding analysis by ELISA revealed that all of the highest antigen-binding clones possessed the same V_(L)-V_(H) gene combinations predicted by the pairing strategy (Table 18).

TABLE 17 Antigen binding of antibody single chain variable fragments (scFvs) from high frequency V_(L) and V_(H) genes. scFv V_(L)-V_(H) pair % V_(L) CDRL3 % V_(H) CDRH3 binding α -OVA 1.1L-1.1H 11.70 WQGTHFPLT 7.11 GSSYYAMDY + SEQ ID NO: 114 SEQ ID NO: 153 1.2L-1.2H 4.40 QQYNSYPLT 1.10 LLWLYAMDY + SEQ ID NO: 115 SEQ ID NO: 155 1.3L-1.3H 3.38 QQSNSWYT 0.57 DVYDGYAMDY + SEQ ID NO: 117 SEQ ID NO: 139 1.4L-1.4H 2.20 QHHYGTPPWT 0.54 NPYAMDY - SEQ ID NO: 119 SEQ ID NO: 140 2.1L-2.1H 5.32 WQGTHFPLT 7.61 RTTVSRDWYFDV + SEQ ID NO: 114 SEQ ID NO: 141 2.2L-2.2H 4.05 QQYNSYPLT 3.23 YYYGSSAMDY + SEQ ID NO: 115 SEQ ID NO: 142 2.3L-2.3H 3.46 QQYSSYPLT 2.22 DGWYYFDY + SEQ ID NO: 116 SEQ ID NO: 143 2.4L-2.4H 2.01 QQHYSTPWT 2.10 EDDYDLFAY + SEQ ID NO: 120 SEQ ID NO: 144 α- C1s 12.95 WQGTHFPQT 7.93 GNYYYAMDY + 1.1L-1.1H SEQ ID NO: 123 SEQ ID NO: 145 6.94 QQWSSYPQLT 7.93 GNYYYAMDY + 1.2L-1.1H SEQ ID NO: 129 SEQ ID NO: 145 3.81 QNDHSYPLT 2.64 DMISYWYFDV + 1.3L-1.2H SEQ ID NO: 130 SEQ ID NO: 146 3.16 QQGQSYPFT 1.67 EDYGNYWYFDV + 1.4L-I.3H SEQ ID NO: 131 SEQ ID NO: 147 3.16 QQGQSYPFT 1.67 EGYYYGSSYFDY − 1.4L-I.4H SEQ ID NO: 131 SEQ ID NO: 148 17.10 FQGSHVPLT 10.99 SDRYDGYFDY + 2.1L-2.1HA SEQ ID NO: 60 SEQ ID NO: 19 17.10 FQGSHVPLT 9.93 SDRFDGYFDY + 2.1L-2.IHB SEQ ID NO: 60 SEQ ID NO: 20 2.62 QQSNEDPWT 3.30 WLLLAY + 2.2L-2.2H SEQ ID NO: 132 SEQ ID NO: 21 2.20 WQGTHFPH 3.30 WLLLAY + 2.3L-2.2H SEQ ID NO: 61 SEQ ID NO: 21 2.20 WQGTHFPH 1.65 SDGYYYFDY + 2.3L-2.3H SEQ ID NO: 61 SEQ ID NO: 23 1.64 QQHYSTPFT 1.15 YYDYDKAYYFDY − 2.4L-2.4H SEQ ID NO: 133 SEQ ID NO: 25  α -Br 1.IL-1.1H 6.64 LQYASSPFT 7.20 HDYGNYVDY + SEQ ID NO: 63 SEQ ID NO: 10 1.2L-1.2H 4.73 WQGTHFPRT 5.62 DGNYQEDYFDY − SEQ ID NO: 64 SEQ ID NO: 11 1.3L-1.3H 4.51 QQNNEDPRT 1.91 EGYAYDVDV + SEQ ID NO: 134 SEQ ID NO: 12 1.4L-I.4H 3.59 QQRSSYPLT 1.20 YDYGKDFDY + SEQ ID NO: 65 SEQ ID NO: 16 2.IL-2.1H 7.24 WQGTHFPQT 2.57 RGDGNYFFDY + SEQ ID NO: 123 SEQ ID NO: 149 2.2L-2.2H 4.50 QQGQSYPWT 2.27 GDEAWFAY − SEQ ID NO: 126 SEQ ID NO: 150 2.3L-2.3H 3.12 LQYASSPYT 2.03 EGDFDY − SEQ ID NO: 135 SEQ ID NO: 151 2.4L-2.4H 2.58 FQGSHVPWT 1.63 GGNYDYAMDY + SEQ ID NO: 136 SEQ ID NO: 152

TABLE 18 Antibody single chain variable fragments (scFvs) identified by by combinatorial pairing of top four V_(L) and V_(H) genes. V_(L)-V_(H) Pairing ELISA Signal^(a) C1s-1 — 1L-1H 4.36 2L-1H 19.92 3L-2H 4.36 4L-3H 6.8 4L-4H 3.7 C1s-2 — 1L-1HB 63.3 3L-1HB 4.65 2L-2H 3.1 3L-2H 4.22 3L-3H 8.8 ^(a)ELISA signal correlates to E. coli whole cell lysates expressing scFvs, measured as the OD₄₅₀ signal of scFvs binding to antigen-coated wells relative to wells coated with unrelated antigen (bovine serum albumin).

Mouse C1s-2 displayed the highest serum titers (Table 19) and therefore, antibodies from this mouse were selected for biophysical characterization of antigen binding affinity by surface plasmon resonance (Biacore). Antibodies were recombinantly expressed and purified as monomeric scFv fragments in E. coli and as full-length IgG antibodies in HEK 293F cells. Pairing of the most abundant light (2.1L) and heavy (2.1H-B) V genes (17.10% and 9.93% CDRL3 and CDRH3 frequencies, respectively) from mouse C1s-2 yielded an antibody with a K_(D) of 20 nM as a scFv (k_(on)=2.3×10⁴ M⁻¹ sec⁻¹; k_(off)=5.0×10⁻⁴ sec⁻¹) and unexpectedly, a slightly lower monovalent K_(D) of 50 nM (k_(on)=2.4×10⁴ M⁻¹ sec⁻¹; k_(off)=1.2×10⁻³ sec⁻¹) as an IgG. From the same mouse, pairing of C1s 2.2L with 2.2H (2.62% and 3.30% CDRL3 and CDRH3 frequencies, respectively) resulted in an IgG that displayed low binding affinity (K_(D) of ˜500 nM, data not shown). However, the pairing of C1s 2.3L with 2.2H (2.20% and 3.30% CDRL3 and CDRH3 frequency, respectively) yielded an IgG with sub-nanomolar binding affinity (K_(D)=0.43 nM, k_(on)=4.5×10⁵ M⁻¹ sec⁻¹; k_(off)=1.9×10⁻⁴ sec⁻¹, FIG. 13 and Table 20), indicating that the natural pairing is likely 2.3L-2.2H. Furthermore, the antibodies were suitable for functional assays, such as sandwich ELISA and immunoprecipitation of C1s from human serum (FIGS. 14-15).

TABLE 19 Serum IgG titers in mice immunized with different antigens. Antigen IgG Titer (serum dilution) Ovalbumin-1 1:5,000  Ovalbumin-2 1:5,000  C1s-1 1:10,000 C1s-2 1:50,000 Bright-1 1:10,000 Bright-2 1:10,000 *IgG titer was determined by maximum mouse serum dilution that gave an ELISA signal above background (binding with pre-immunized mouse serum).

TABLE 20 Biophysical characterization of antibody single chain variable fragments (scFv) and IgGs derived by mining the bone marrow plasma cell repertoire of mouse Cls-2, which displayed the highest serum IgG titer. V_(L)-V_(H) pair % V_(L) % V_(H) CDRL3 CDRH3 k_(on)(M⁻¹ sec⁻¹) k_(off)(sec⁻¹) K_(D)(nM) 2.1L-2.1HB (scFv) 17.10 9.93 FQGSHVPLT SDRFDGYFDY 2.3 × 10⁴ 5.0 × 10⁻⁴ 20 SEQ ID NO: 60 SEQ ID NO: 20 2.1L-2.1HB (IgG) 17.10 9.93 FQGSHVPLT SDRFDGYFDY 2.4 × 10⁴ 1.2 × 10⁻³ 50 SEQ ID NO: 60 SEQ ID NO: 20 2.3L-2.2H (IgG) 2.20 3.30 WQGTHFPH WLLLAY 4.5 × 10⁵ 1.9 × 10⁻⁴ 0.43 SEQ ID NO: 61 SEQ ID NO: 21

Methods of immunization, isolation of bone marrow plasma cells, preparation of variable light (VL) and variable heavy (VH) genes, and high-throughput sequencing of VL and VH repertoires were essentially the same as described in Examples 1-4 unless otherwise stated.

Bioinformatic Analysis:

(1) CDR3 Identification

A search method was developed based on conserved flanking sequence motifs found upstream and downstream of CDR3. Searching motifs for CDRH3 and CDRL3 were determined based on amino acids that occur with an average frequency of 99% at specific positions in V genes from the Kabat database (Table 3). V_(H) sequences were searched for the motif DXXX(Y/F)(Y/F)C (Kabat #86-92; SEQ ID NO: 802) and WGXG(T/S) (Kabat #103-107; SEQ ID NO: 803) at N- and C-termini of CDRH3, respectively. Analogously, V_(L) genes were found by searching for the motifs DXXXY[F/Y]C (Kabat #82-88; SEQ ID NO: 804) and FGXGT (Kabat #98-102; SEQ ID NO: 805). This approach correctly identifies over 94% of V_(H) and 92% of V_(L) full-length sequences in the Kabat database. Any sequences or reverse complements containing these motifs were extracted as either V_(H) or V_(L) genes, respectively. Only the sequences with in-frame CDR3 and without stop codons were further analyzed. For each sample, the most highly represented CDR3 sequences (typically represented at frequencies >1%) were discovered, and their relative abundances in all other the 7 samples were calculated. To find a consensus full-length V_(H)/V_(L) gene sequence, sequences containing high frequency CDR3s of interest were analyzed for pairwise homology by BLAST, and the sequence with the highest score was chosen. FIG. 5 summarizes the bioinformatics analysis of the V gene sequences. Analysis was performed using Perl scripts in a Unix environment, which were converted into a graphical user interface using the Matlab 7.1 gui builder for enhanced visualization of results.

(2) Analysis of CDR3 Expression Across Samples from Different Mice.

CDR3 sequences found in multiple samples were extracted and analyzed for their prevalence in all mice. First, Principle Component Analysis (PCA) was performed using Matab to analyze the variance of CDR3 expression in different mice (FIGS. 10A-10B). The majority of the variance between mouse samples was categorized into seven principle components. Second, the percent of CDRH3 sequences found in multiple samples were calculated. Since, it could not be determined whether replicate sequences were due to contamination or a true biological effect, a permutation test was performed to determine whether the percentage of sequences shared across four samples was biased by samples analyzed on a specific day. The percent of shared sequences was calculated for all 70 possible combinations of the eight samples selected four times, subsequently ranked by percentage overlap. The top three ranked combinations were considered significant and not attributed to random combinations.

(3) Frequency Distribution of Abundant CDRH3.

A heat map was generated to illustrate the prevalence of highly abundant CDRH3s from each sample in mice receiving different antigen. Only CDRH3 sequences with statistically significant frequencies in the top 5% of the distribution (frequency cut-off ˜0.03%) were represented (FIG. 9).

(4) Homology Analysis of Full-Length V Genes.

Full-length V genes were found for sequences containing identical CDR3s. First, sequences were placed in-frame by docking CDR3 motifs. Second, full-length V gene sequences were accepted if they did not contain stop codons and covered all three CDR regions. Non-identical, full-length V genes (containing at least one amino acid difference) were aligned to determine pairwise homology using the multiple sequence alignment tool in Geneious Software (Biomatters Ltd., FIGS. 8A-8C and Table 14).

(5) Germline Analysis.

The top 4 full-length consensus V_(L) and V_(H) genes were analyzed by the IMGT/V-Quest Tool (Brochet et al., 2008). Additionally, the top 30 ranked CDRH3 sequences, of four mice (adjuvant-1, adjuvant-2, C1s-1, and C1s-2) were further analyzed for V(D)J recombination using IMGT/V-QUEST tool. The V segment germline usage and V_(H) gene somatic mutations were identified after the IMGT/V-QUEST analysis. These data are reported in FIG. 7 and Table 13.

Construction of Synthetic Antibody Genes.

Synthetic antibodies can be constructed in accordance with the methods described in the Example 8 above.

Surface Plasmon Resonance (Biacore)

C1s was covalently immobilized on a CM5 chip (GE healthcare, NJ) at a level of approximately 200 response units via standard amine coupling chemistry as described in the manufacturer's protocol. BSA was similarly coupled for baseline correction. All kinetic analyses were performed at 25° C. in HBS-EP (10 mM HEPES, 150 mM NaCl, 50 μM EDTA, 0.005% P-20, pH 7.4) on a BIAcore 3000 (GE healthcare, NJ). Antibodies were injected over immobilized antigen at a flow rate of 50 μl/min or 100 μl/min and the chip was regenerated with a single 10s injection of 20 mM NaOH. Each sensogram was run in duplicate. Kinetic and equilibrium constants were determined by global fitting to a bivalent model using BIAevaluation software (GE healthcare, NJ).

Example 10 Rapid Generation of Monoclonal Antibodies Directly from Lymphoid Tissues without B Cell Isolation Immunization Protocol

Protein antigens (e.g., purified hen egg lysozyme or keyhole limpet hemocyanin)) were resuspended in sterile-filtered phosphate buffered saline (PBS) at 1.0 mg/ml. On the day of primary immunization, 200 ul of antigen solution was thoroughly mixed with 200 ul of Complete Freund's Adjuvant (CFA, Pierce Biotechnology) and 600 ul of sterile PBS and stored on ice. Animal species (rabbits, sheep, goats, pigs) mice were bled approximately 20 ml of blood was collected and stored at −20° C. for later analysis. Day 1 was designated as the day primary immunizations were performed. 1.0 ml of the antigen-CFA mixture per animal was injected with a 21-gauge needle subcutaneously.

For subsequent booster immunizations, 200 ul of antigen solution was thoroughly mixed with 200 ul of Incomplete Freund's Adjuvant (IFA, Pierce Biotechnology) and 600 ul of sterile PBS and stored on ice. Animals were given booster immunizations every 14 days, injections were given intraperitoneally at 1.0 ml of antigen-IFA mixture per animal. Animals were bled 7 days following the booster immunization and antigen-specific antibody titers were measured to monitor immune responses. When immune responses reached high titers (>1/100,000 serum dilution), animals were sacrificed and blood and tissue was harvested.

Isolation Bone Marrow, Lymph Nodes, and Spleen

Bone Marrow:

The muscle and fat tissue was removed from femurs harvested from immunized animals. Using an electric drill and sterilized drill bit, holes were drilled into the ends of both tibia and femurs to provide enough space for a 22-gauge needle to enter the bone. Bone marrow was flushed out using this procedure. Bone marrow tissue was collected in sterile-filtered Buffer#1 (PBS/0.1% bovine serum albumin (BSA)/2 mM ethylenediaminetetracetic acid (EDTA)). Bone marrow cells were collected by filtration through a 70-um cell strainer (BD) with mechanical disruption, washed with 40 ml of PBS and collected in a 50 ml tube (Falcon, BD). Bone marrow cells were then centrifuged at 1200 RPM for 10 mM at 4° C. Supernatant was decanted and cell pellet was resuspended with 5.0 ml of RBC lysis buffer (eBioscience) and shaken gently at 25° C. for 5 minutes. Cell suspension was then diluted with 40 ml of PBS and centrifuged at 1200 RPM for 10 minutes at 4° C. Supernatant was decanted and cell pellet was resuspended in 2.0 ml of Buffer#1.

Lymph Nodes:

Lymph nodes were harvested from animals, placed in Buffer#1 and stored on ice. Using two 22-gauge needles, lymph node tissue was teased apart into small 1-2 mm fractions. Fractions were then placed in a petri dish, with 5 ml of Buffer#1. Next, 0.5 ml of 10× collagenase D (R&D Systems) was added to each lymph node tissue fraction and incubated at 37 C for 30 minutes. Following incubation, 100 ul of 100 mM EDTA is added to the lymph node fractions (to quench collagenase). Lymph node fragments were then transferred to a 70-um cell strainer and with mechanical disruption were washed with 40 ml of PBS. Lymph node cells were then centrifuged at 1200 RPM for 10 min at 4 C. Supernatent was decanted and cell pellet was resuspended in 20 ml of PBS and centrifuged at 1200 RPM for 10 min at 4 C. Supernatent was decanted and cell pellet was resuspended in 2.0 ml of Buffer#1.

Spleen:

Spleens were harvested from animals and placed in Buffer#1 and stored on ice. Using two 22-gauge needles, spleen tissue was teased apart into small 1-2 mm fractions. Fractions were then placed in a petri dish, with 5 ml of Buffer#1. Next, 0.5 ml of 10× collagenase D (R&D Systems) was added to each spleen tissue fraction and incubated at 37 C for 30 minutes. Following incubation, 100 ul of 100 mM EDTA is added to the spleen fractions (to quench collagenase). Spleen fragments were then transferred to a 70-um cell strainer and with mechanical disruption were washed with 40 ml of PBS. Spleen cells were then centrifuged at 1200 RPM for 10 min at 4 C. Supernatant was decanted and cell pellet was resuspended with 5.0 ml of RBC lysis buffer (eBioscience) and shaken gently at 25° C. for 5 minutes. Cell suspension was then diluted with 40 ml of PBS and centrifuged at 1200 RPM for 10 minutes at 4° C. Supernatent was decanted and cell pellet was resuspended in 2.0 ml of Buffer#1.

Preparation of mRNA.

Cell isolated as described herein were centrifuged at 2,000 RPM at 4° C. for 5 min. Supernatant was decanted, and cell pellets were then resuspended and lysed with TRI reagent and total RNA was isolated according to the manufacturer's protocol in the Ribopure RNA isolation kit (Ambion). mRNA was isolated from total RNA through with oligodT resin and the Poly(A) purist kit (Ambion) according to the manufacturer's protocol. mRNA concentration was measured with an ND-1000 spectrophotometer (Nanodrop).

Preparation of Antibody VL and VH Genes Using 5′ RACE.

cDNA libraries of the VL and VH genes from antibodies of a desired class (IgA, IgG, IgM or IgE) were constructed from the isolated mRNA. To start first strand cDNA was synthesized from mRNA using the SMARTscribe Maloney Murine leukemia virus cDNA was prepared from mRNA using reverse transcriptase (MMLV-RT, Clonetech). The cDNA synthesis utilized 300 ng mRNA template switching 5′ adaptor primers and oligo(dT) 3′ primers. Subsequently, 5′ RACE was performed by using RNA ligation according to the RLM-RACE First Choice kit (Ambion), according to the manufacturer's instructions. 2 μl of unpurified cDNA was used as a template. 5′ Primers, buffers, polymerase, and reaction conditions were provided by manufacturer (Clontech and Ambion). 3′ primers were designed based upon Ig μ or γ or constant region sequences of other species, which are publicly available from the IMGT database. 3′ constant region specific primers for various species are shown in Table 21. PCR products were purified with a 1% agarose gel, bands at ˜400-450 bp correlated to VL and VH and were isolated and submitted for 454 high-throughput DNA sequencing.

V Gene Amplification by PCR Using Primer Mixes.

Isolated mRNA was used for first strand cDNA synthesis by reverse transcription with the Maloney murine leukemia virus reverse transcriptase (MMLV-RT, Ambion). For cDNA synthesis, 50 ng of mRNA was used as a template and oligo(dT) primers were used; RT-PCR was performed according to manufacturer protocol of Retroscript kit (Ambion). Following cDNA synthesis VH and VL genes were amplified by PCR using 2 ul of unpurified cDNA product. 5′ primer mixes for VL and VH were generated based on germline repertoire sequences available on the IMGT database. An example of 5′ regions of VH genes in sheep is provided in FIG. 16. 3′ primers were used based on constant regions, as described in Table 21. PCR products of the VL and VH genes were gel purified and submitted for 454 DNA sequencing.

TABLE 21 Constant region 3′ primers CH1 Tm 3′ primer sequence region (° C.) Rabbit IGHG*01 GGG AAG ACT GAC GGA GCC TTA GGT TGC 1 to 28 65.6 C (SEQ ID NO: 172) IGHG*02 GGA AGA CTG ATG GAG CCT TAG GTT GCC 1 to 28 64 C (SEQ ID NO: 173) IGHG*05 GGG TAC AGA GTT GGA GAT GAC AGG CTC 1 to 28 62.8 A (SEQ ID NO: 174) IGHM GGG TAC AGA GTT GGA GAT GAC AGG CTC 1 to 29 63.1 AC (SEQ ID NO: 175) Sheep IGHG1 GGT AGA CTT TCG GGG GTG TTG TTG AGG 1 to 28 64.3 C (SEQ ID NO: 176) IGHG2 CTT TCG GGG CTG TGG TGG AGG C (SEQ ID 1 to 22 65 NO: 177) IGHM GGA AGA CTT TCG GGT GAG ATT CAC TTT 1 to 28 59.1 C (SEQ ID NO: 178) Pig IGHG1, 2A, GAT GGG GCC GTC TTG GGG GC (SEQ ID 1 to 20 66.1 3, 5 NO: 179) IGHG2B AAT GGG GCC GTC TTG GGG GC (SEQ ID 1 to 20 65.7 NO: 180) IGHM*01 GTA GAG ATT CGG GGC AGA CTG GCT CT 1 to 26 63.3 (SEQ ID NO: 181) IGHM*02 GGA CGG GAA GTC CTG GAT GTT CTG GC 1 to 26 64.6 (SEQ ID NO: 182) Isolation of VH and VL cDNA by Hybridization.

Isolated mRNA was used for first strand cDNA synthesis by reverse transcription with MMLV-RT (Ambion). For cDNA synthesis, 200 ng of mRNA was used as a template and 3′ specific primers for V_(L) and V_(H) constant regions (Table 21) were used in the RT reaction; RT-PCR was performed at 55 C for 90 min followed by 90 C for 10 min. Following RT-PCR, RNase was added to the reaction to deplete remaining mRNA. Next, 10 μM of biotinylated primers were added to the cDNA. Biotinylated primers were based on the reverse complement of primers described in Table 21 and contained an overhang on the 3′ end of 454 sequencing Primer B. 25 ul of streptavidin coated Dynabeads (Invitrogen) were added to the cDNA and rotated for 5 min at room temperature. The tube was then placed on the magnet and supernatant was removed and discarded, the cDNA-bead complex was then washed twice with 200 ul of PBS. cDNA was then eluted from the beads with 20 ul of 10 mM Tris-HCl, pH 7.5, mixture was heated at 70 C for 2 min and then placed on the magnet. The eluted cDNA in the supernatant and transferred to a new tube, then gel purified by a 1% agarose gel, and bands ˜600-700 nt corresponding in size to IgL and IgH cDNAs were excised and processed for 454 DNA sequencing.

Bioinformatic Analysis for CDR3 Identification.

CDR3 is the most diversified region of antibody and dominates antigen recognition. The inventors realized that the sequences flanking CDR3 are highly conserved in all the species that have an immunoglobulin-encoding adaptive immune response system (fish, frog, birds, mammals, etc). These conserved motifs are believed to be essential to provide a rigid conformation context for properly presenting the ultra-variable CDR3 loop while keeping the overall structure of variable domain undisturbed. The inventors develop a fast algorithm for identifying the CDR3 based on probabilistic homology analysis. Three strategies can be used to design searching motifs for individual specie—using antibody database (rearranged genes), germline genes, or genomic sequences of immunoglobulins. This bioinformatics analysis method could be therefore applied for antibody sequences of nearly all the species carrying adapted immune systems, even without large antibody databases. The inventors developed a fast algorithm for identifying the CDR3 based on probabilistic homology analysis. Three strategies were used to design searching motifs for individual specie—using antibody database (rearranged genes), germline genes, or the genomic sequences of germline immunoglobulin segments from the genome sequence of the animal. This bioinformatics analysis method could be therefore applied for antibody sequences of nearly all the species carrying adapted immune systems, even without large antibody databases.

Design of Rabbit CDR-H3 Homology Search Motifs.

A Perl script was written to calculate amino acid occurrence frequency at each residue position alone antibody variable domain by alignment of 506 rabbit VH genes in KabatMan database. Calculation result revealed the existence of highly conserved sequences flanking CDR-H3 regions (Kabat numbering residues #95-102). For example 99% of rabbit VH genes have cysteine and glycine at the position of 92 and 106, respectively. 10 highly conserved positions flanking CDR3 (>90%) were identified. Tables 22-23 list the calculated amino acid occupancy probabilities at these positions. To efficiently identify antibody sequences with somatic hypermutation located at motif regions, a possibility weight is evenly given to any non-dominant amino acids. For example, at position 86, possibility for aspartic acid is 0.97, possibility for alanine is 0.03, and possibility for any one out of the other 18 amino acids is 0.03/18=0.00167.

TABLE 22 5′ searching motif for rabbit CDR-H3 and associated probability matrix Kabat # 85 86 90 91 92 93 94 Residue (possibility) A 0.83 D 0.97 Y 0.94 F 0.83 C 0.99 A 0.93 R 0.92 E 0.07 A 0.03 A 0.05 Y 0.09 X 0.01 G 0.02 S 0.04 T 0.05 X 0.03 X 0.01 M 0.03 V 0.02 X 0.04 X 0.05 X 0.05 X 0.03

TABLE 23 3′ searching motif for rabbit CDR-H3 and associated probability matrix Kabat # 103 104 105 106 107 108 Residue W 0.97 G 0.94 P 0.90 G 0.99 T 0.92 L 0.98 (possibility) X 0.03 I 0.04 W 0.05 X 0.01 P 0.07 X 0.02 X 0.02 Q 0.03 X 0.01 X 0.02

Chicken CDR-H3 Search Motif Derived from Germline Sequence Analysis Using Genomic Data.

When an antibody sequence database is not available, search motifs can be identified from the germline sequences available from genomic information. As an illustrative example, the search motif for the 5′ of VDR3 in chicken was identified and the respective probability Table 24 was constructed. All 18 chicken germline IGHV genes, including both functional and pseudogenes, were extracted from the database. FIG. 17 displays the aligned protein sequences of all chicken heavy chain v-segment genes. A conserved motif flanking the 5′ of the CDR3 was then calculated as above.

TABLE 24 5′ searching motif for chicken CDR-H3 and associated possibility matrix Kabat # 85 86 87 90 91 92 93 94 Residue E 0.98 D 0.98 T 0.98 Y 0.93 Y 0.83 C 0.99 A 0.55 K 0.58 (probability) X 0.02 X 0.02 X 0.02 S 0.05 F 0.09 X 0.01 T 0.44 R 0.41 X 0.02 L 0.03 X 0.01 X 0.01 X 0.02

Analysis of antibody variable heavy and variable light chain sequences was performed essentially as described in Example 5. The conserved motifs as exemplified above were used to search for CDR3 regions. Construction of synthetic antibody genes based on identified abundant variable region sequences was essentially as described in Example 7. Antibody expression and binding analysis was essentially as described in Example 8.

Example 11 Rapid of V Gene Repertoires from Total Lymphoid Tissues without B Cell Isolation Following Immunization of Different Animals

Protein antigens (purified hen egg lysozyme or Concholepas concholepas hemocyanin)) were resuspended in sterile-filtered phosphate buffered saline (PBS) at 10 mg/ml. On the day of primary immunization, 100 μg of antigen diluted in 1 mL saline was mixed with 1 ml of Complete Freund's Adjuvant (CFA) and stored on ice. Animal species (rabbits, sheep, or goats) were bled on day 0 (pre-immunization bleed) into two heparin tubes to obtain approximately 15 mL blood for subsequent RNA isolation and serum titers. Day 1 was designated as the day primary immunizations were performed. 2.0 ml of the antigen-CFA mixture per animal was injected.

For subsequent booster immunizations, 100 μg of antigen diluted in 1 mL saline was mixed with 1 ml of Incomplete Freund's Adjuvant (IFA) and stored on ice. Animals were given booster immunizations every 14 days, injections were given at 2.0 ml of antigen-IFA mixture per animal. Animals were bled 6 days following the booster immunization and antigen-specific antibody titers were measured to monitor immune responses. When immune responses reached high titers (>1/25,000 serum dilution, see Table 25), animals were sacrificed and blood and tissue was harvested.

TABLE 25 Serum titers against HEL and CCH in all eight injected animals Animal Titer^(a) Rabbit CCH1 1:3,125,000 Rabbit CCH2 1:625,000 Rabbit HEL1 1:5,000 Rabbit HEL2 1:25,000 Goat 52 1:625,000 Goat 53 1:125,000 Sheep 54 1:625,000 Sheep 55 1:25,000 ^(a)Titer was against injected antigen (HEL except for the two CCH rabbits) as determined by ELISA using a secondary antibody against species-specific IgG + IgM

Isolation of Bone Marrow, Spleen, and PBMCs

Bone Marrow:

The muscle and fat tissue was removed from femurs and humeri harvested from immunized animals. Using a Dremel saw, bones were cross-sectioned directly adjacent to the joints. Bone marrow was flushed out with sterile PBS with the aid of a small spatula to break up cellular masses of the red marrow. Bone marrow cells were collected by filtration through a 70-μm cell strainer (BD) with mechanical disruption, washed with 40 ml of PBS and collected in a 50 ml tube (Falcon, BD). Bone marrow cells were then centrifuged at 1200 RPM for 10 min at 4° C. Supernatant was decanted and cell pellet was resuspended with 5.0 ml of RBC lysis buffer (eBioscience) and shaken gently at 25° C. for 5 minutes. Cell suspension was then diluted with 40 ml of PBS and centrifuged at 1200 RPM for 10 minutes at 4° C. Supernatant was decanted and cell pellet was resuspended in 1.0-2.0 ml of Buffer#1.

Spleen:

Spleens were harvested from animals and placed in sterile PBS and stored on ice. Using two razor blades, spleen tissue was diced and then teased apart into small 1-2 mm fractions. Fractions were then placed in a petri dish, with 5 ml of Buffer#1. Spleen fragments were then transferred to a 70-um cell strainer and with mechanical disruption were washed with 40 ml of PBS. Spleen cells were then centrifuged at 1,200 RPM for 10 min at 4 C. Supernatant was decanted and cell pellet was resuspended with 5.0 ml of RBC lysis buffer (eBioscience) and shaken gently at 25° C. for 5 minutes. Cell suspension was then diluted with 40 ml of PBS and centrifuged at 1200 RPM for 10 minutes at 4° C. Supernatent was decanted and cell pellet was resuspended in 1.0-2.0 ml of Buffer#1.

Blood:

Blood was collected from animals into sealed heparin tubes and stored on ice. Blood was collected at day 0, six days after every booster injection, and at sacrifice of each animal. Blood at various time points (day 0, day 20, day 34 for all animals, as well as at sacrifice for each animal) was processed to isolate PBMCs for subsequent isolation of RNA. PBMC purification was accomplished by layering each bleed (16-20 mL for each animal) on top of histopaque solution (Sigma) at 1:1 volume, avoiding mixing of the contents. The blood-histopaque solution is centrifuged at 1,600 RPM for 30 minutes at 23° C. without centrifugation braking. The peripheral blood mononuclear cell (PBMC) layer is isolated following gradient centrifugation, and washed through centrifugation with wash buffer (PBS). Cells were then resuspended in 1.0-2.0 Buffer#1. The top layer containing 10-12 mL serum was collected for analysis of serum titers against the respective antigen. Cardiac punctures at the time of sacrifice for each animal yielded approximately double the volume of blood. Serum volumes from these bleeds contained 30-50 mL.

Cells isolated as described herein were centrifuged at 2,000 RPM at 4° C. for 5 mM. Supernatant was decanted, and cell pellets were then resuspended by vigorous pipetting and vortexing in 1 mL TRI reagent and total RNA was isolated according to the manufacturer's protocol in the Ribopure RNA isolation kit (Ambion). RNA concentration was measured with an ND-1000 spectrophotometer (Nanodrop).

200-700 ng of total RNA in a volume of 2.75 ul was used for first strand cDNA synthesis with the SMARTer RACE cDNA amplification kit (Clontech). 1.0 ul of CDS Primer A was added to the RNA, followed by incubation in a thermal cycler at 72° C. for 3 minutes, then to 42° C. for 2 minutes. 1 ul of the SMARTer IIA oligo was added, followed by 5.25 ul of a master mix including 2.0 ul 5× First-Strand Buffer, 1.0 ul 20 mM DTT, 1.0 ul of 10 mM dNTP mix, 0.25 ul RNase inhibitor (40 U/ul), and 1.0 ul SMARTScribe Reverse Transcriptase (100 U). The first strand synthesis reaction mixture was then incubated at 42° C. for 90 minutes, followed by 70° C. for 10 minutes. The first strand cDNA product was diluted with 100 ul of Tricine-EDTA Buffer. The 5′ RACE amplification was setup with a master mix including 70.5 ul RNase-free water, 10 ul 10× Advantage 2 PCR Buffer (Clontech), 2.0 ul 10 mM dNTP mix, 10 ul 10× Universal Primer A Mix (Clontech), and 1.5 ul Advantage 2 Polymerase Mix (Clontech). 94 ul of master mix was added to a PCR tube containing 2.0 ul of first strand cDNA product and 1.0 ul of a 3′ primer (10 μM). For VH amplification, 3′ primers were designed based upon Ig mu or gamma CH1 gene sequences of rabbit, sheep, or goat, which are publicly available from the IMGT database (rabbit and sheep) or Genbank (goat). For VL amplification, 3′ primers were designed based upon Ig kappa or lambda gene sequences of rabbit, sheep, or goat, which are publicly available from the IMGT database (rabbit kappa) or Genbank (rabbit lambda, sheep and goat). 3′ constant region specific primers for each species are shown in Table 26. PCR products were purified with a 1% agarose gel, bands at ˜500-550 bp correlated to VL and VH and were isolated and submitted for 454 high-throughput DNA sequencing.

TABLE 26 Constant region 3′ primers SEQ CH1/Cκ/ ID Cλ 3′ primer sequence NO:  region Rabbit IGHG1 CAGTGGGAAGACTGACGGAGCCTTAG 184  5 to 30 IGHG2 CAGTGGGAAGACTGATGGAGCCTTAG 185  5 to 30 IGHM GGAGACGAGCGGGTACAGAGTTGGAG 186 13 to 38 IGκ TGGTGGGAAGAKGAGGACAGTAGG 187 15 to 38 IGλ1 CAAGGGGGCGACCACAGGCTGAC 188  2 to 24 IGλ2 GTGAAGGAGTGACTACGGGTTGACC 189  1 to 25 IGλ3 GAGGGGGTCACCGCGGGCTGAC 190  2 to 23 Sheep IGHG1 GACTTTCGGGGGTGTTGTTGAGG 191  1 to 23 IGHG2 GACTTTCGGGGCTGTGGTGGAGG 192  1 to 23 IGHM CCAGGGGGAAGACTTTCGGGTGAGATTC 193  6 to 33 IGκ GATGGTTTGAAGAGGGAGACGGATGGCTGAGC 194  9 to 40 IGλ ACAGGGTGACCGAGGGTGCGGACTTGG 195  8 to 34 Goat IGHG GACTTTCGGGGGTGTGGTGGAGG 196  1 to 23 IGHM CCAGGGGGAAGACTTTCGGGTGAGATTC 197  6 to 33 IGκ GATGGTTTGAAGAGGGAGACGGATGGCTGAGC 198  9 to 40 IGλ ACAGGGTGACTGAGGGTGCGGACTTGG 199  8 to 34

The V gene repertoire prepared by 5′ RACE of unfractionated lymphoid tissues described above was compared with the V gene repertoire obtained by first sorting antigen secreting B cells (CD138+ plasma cells and plasmablasts) followed by 5′ RACE amplification of the V gene mRNAs as described above. CD138+ cells were purified by magnetic sorting using rat α-murine CD138 antibody clone 281-2 (BD Pharmingen) as described in Example 2. The V gene DNA obtained from unfractionated lymphoid tissue was designated total lymphoid tissue V gene (tLT-V). DNA obtained from isolated antibody secreting CD138+ B cells was designated as Plasma cell V gene (PC-V). The tLT-V and the PC-V DNA was sequenced using NExtGEn sequencing as described in Example 4 and the data was processed as described in Example 5. The inventors established that more than 95% of the abundant CDRH3 sequences (minimum of 10 reads or ≧0.04%) in the PC-V pool are also detected in the tLT-V pool when comparing rabbit HEL1 tLT-V and PC-V, which both approximately the same number of aligned reads. Table 27 shows a comparison of the most abundant VH sequences detected in the tLT-V sample and in the PC-V sample obtained from bone marrow plasma cells for four rabbits immunized with CCH (CCH1 and CCH2) or with HEL (HEL1 and HEL2).

TABLE 27 Comparison of most abundant VII genes identified from the sequencing of the repertoire from V gene cDNA prepared from total lymphoid tissue (tLT-V) or from purified CD138+ B cells (PC-V) top 10 PC-V CDRH3 tLT-V^(a) SEQ ID NO: Rabbit CCH1 ARGLNAAGYTTFAYGTTVMDL + 200 ARDMDGGNVGYGM + 201 ARFDAAYADFGVANL + 202 ARADRGFYAGTSDYTGYNL + 203 ARADRGFYAGTSDYSGYNL − 204 ARDAGGSYSYYFDL − 205 ARDAGGYTGDGYYFKL − 206 ARGGPIHYSNL + 207 ARGSGWYGGLNL + 208 ASNYADPPGYNYTPFNL + 209 Rabbit CCH2 ATDRGPSGSGPLDL + 210 SRDGKYAGIAGYGSTYFDL + 211 AGDGRSYYADYAFVDL + 212 ARDPVTRLVAGADYFDL + 213 ARDVYTYDADGDYRHFNL + 214 ARAPVYYNGGYAGFREFNL + 215 ARDGGWGYNL + 216 ARDSFDGYGDFNL − 217 ARVGNHYGMDL − 218 ARGAAGYAGYAYAYYYFDF − 219 Rabbit HEL1 ARDWNYGMDL + 220 ARNFAL + 221 ARDLNAAHRTNSPKL + 222 WITNL + 223 ARGFSLLGYLTL + 224 ARDPYGRSGDDFVL + 225 ARGYDDYGDYLDL + 226 ARSAYNDFGDYVSPLTL − 227 ARQYLL + 228 ARGSVIYVGEL + 229 Rabbit HEL2 ARGRSDTNYRLNL + 230 GRSVEAVQGASNWYFDI + 231 GKTSTIDSDYYNL + 232 ARGGFTDRTYANI − 233 ARNAGGNDYFRL − 234 GRYGGNVGAFDM + 235 ARGNSVTDTYLIDSGMDL + 236 AKSAYNTAGYSPL + 237 ARDLSYDPYGDLGTRLDL − 238 ARRNPNYDTGHFNI + 239 ^(a)Present (+) or absent (−) in the top 15 most abundant CDRH3 of tLT-V repertoire.

Example 12 Isolation of Monoclonal Antibodies by Mining the IgG Variable Gene Repertoire of Bone Marrow, Spleen, and PBMC Cell Populations—Application to Rabbit, Sheep, and Goat

V gene cDNAs from different lymphoid organs or from peripheral blood were sequenced, as described in Examples 4 and 9, and 454 reads were processed by rapid bioinformatic analysis that relied on homologies to conserved framework regions within V genes in order to identify the most common complementarity determining region 3 (CDR3) sequences. Germline alignments were performed using the IMGT software HighV-Quest. Sheep germline sequences, which have been shown to have high identity to known goat sequences, were used for IMGT-based alignment to determine CDR motifs in goats.

Bioinformatic analysis of repertoires in rabbit, sheep, and goat revealed distinct differences as compared to murine repertoires. Primarily the repertoire polarity in the tBM samples for both heavy and light chain was lower than in the mice (Example 9). Thus, unlike the mice where antigen-specific V gene were identified solely based on relative cDNA abundance additional bioinformatics schemes were implemented to refine the data and aid the antigen-specific V gene identification. In one method, described herein PBMC repertoires to compare to bone marrow data. Antigen secreting cells in the bone marrow in other lymphoid compartments at early times following booster immunization (between 4-30 days, depending on species). Sequences present at high frequency in the bone marrow and also at moderate to high frequencies in other compartments account for antigen-specific monoclonal antibodies. The use of IgG-specific 5′ RACE amplification affords the high resolution analysis of class-switched (IgG, IgA or IgE encoding) antibodies expressed predominantly by circulating plasmablasts and plasma cells (and to a lesser extent because of substantially lower transcription level, by class switched memory cells) in total peripheral blood monocytes without the need for prior purification of specific B cell populations. It should be noted that transcript levels (and thus cDNA levels) from class-switched memory B cells are much lower, as these cells do not actively secreting immunoglobulin. Table 28 contains the top 10 V_(H) sequences for four of the five animals above the titer threshold of 1:25000, from both bone marrow and PBMC populations. As expected, correlation of the two populations is not immediately obvious and additional filters are necessary to select sequences common to both.

TABLE 28 Frequencies (%) of the most highly represented CDRH3 sequences in bone marrow and PBMCs. Total bone marrow Total PBMC SEQ SEQ CDRH3 Percent ID CDRH3 Percent ID Goat 52 GRGRYGGGYDYDFFQYGVDV 1.39 240 ARRCGEGDGYGYNPDCYDY 0.34 241 VRCYTHWSDNNGRCYGPMY 0.31 242 ARERSGWYSPYGAVDV 0.25 243 AKYFWTNNYADYVFFDI 0.25 244 ARDGDGAGGALSSGLDV 0.24 245 GRDGYYSDYYAVDV 0.24 246 ARSNGGGIGDVDV 0.17 247 GRGYDQVVS 0.23 248 VRSDYGYGAGYGWGFHH 0.13 249 ADGYSYPNAY 0.22 250 GRDGYYSDYYAVDV 0.12 246 TKSWDYDYANGAEF 0.22 252 VREAYGSDGLYYGIDV 0.12 253 GRDV 0.20 254 VTGGNGYGYDAP 0.12 255 ARGYSDYAYFYGGAIEV 0.17 256 ADGYSYPNAY 0.12 250 GKGVYYNYGADVED 0.17 258 ASAYGYSWNSYGIDD 0.11 259 Sheep 54 ARGPDYSTYGTAYIYYLDY 0.40 260 ASSILAISNY 0.77 261 ARGPDYSTYGSYYLYYLDY 0.38 262 AT SAC GYTHCIDY 0.53 263 ARGGGDY 0.35 264 ARYRYFAESLIDY 0.49 265 ASSILAISNY 0.35 261 VTGNMYSCDVDF 0.47 267 ARCHYGGHCETYGLPMDY 0.32 268 ARGLMPIFDR 0.45 269 VRDYEEYNHAYAYGGY 0.29 270 IREGGGGYGFNIDY 0.38 271 ECYNGYGYAYGYNIDT 0.27 272 VRVRRGYGHAYGYNDY 0.34 273 GREGNIAYGYDYGPHNID 0.24 274 GREGNIAYGYDYGPHNIDYY 0.30 274 ARNTGRYGICSTIDA 0.23 276 GRESRSVSGYGHGVTNFDF 0.27 277 ARGCLLIDY 0.22 278 ECYNGYGYAYGYNIDT 0.26 272 Bone marrow plasma cells^(a) Total PBMC SEQ SEQ CDRH3 Percent ID CDRH3 Percent ID Rabbit CCH1 ARGLNAAGYTTFAYGTTVMDL 0.93 280 ATYDGSIAYLAL 1.47 281 ARDMDGGNVGYGM 0.88 282 AKYSASSGAYYDGYYFNL 0.71 283 ARFDAAYADFGVANL 0.63 284 ARASSSSGHYYDGYYFNL 0.64 285 ARADRGFYAGTSDYTGYNL 0.60 286 ARGGYSTFDL 0.29 287 ARADRGFYAGTSDYSGYNL 0.51 288 ARDLVMLSYL 0.28 289 ARDAGGSYSYYFDL 0.47 290 ASNYAGNPGYGYAPFNL 0.28 291 ARDAGGYTGDGYYFKL 0.42 292 ARADRGFYAGTSDYSGYNL 0.24 293 ARGGPIHYSNL 0.40 294 ARNFKL 0.24 295 ARGSGWYGGLNL 0.40 296 ARGDDDYWYYLNL 0.23 297 ASNYADPPGYNYTPFNL 0.35 298 ERHRHGDAYPNL 0.23 299 ATDRGPSGSGPLDL 0.71 300 AREGGNSDWSFTL 1.05 301 SRDGKYAGIAGYGSTYFDL 0.67 302 ARDSSYNYWVPDYFDL 1.04 303 AGDGRSYYADYAFVDL 0.56 304 AREHDDDNGALTL 1.00 305 ARDPVTRLVAGADYFDL 0.48 306 ARYYIYRGDWSGNL 0.94 307 ARDVYTYDADGDYRHFNL 0.47 308 ARMGGSDEDYHL 0.87 309 ARAPVYYNGGYAGFREFNL 0.46 310 ARDPFASSSGYYWWGMDL 0.65 311 ARDGGWGYNL 0.46 312 ARDSSSGGNRGFDL 0.61 313 ARDSFDGYGDFNL 0.45 314 ARLRSSSGYFIYDL 0.45 315 ARVGNHYGMDL 0.45 316 ARGEYGTKLDV 0.42 317 ARGAAGYAGYAYAYYYFDF 0.44 318 ARCGGFGIEYFNL 0.42 319

Filtering by Mutual Abundance in Bone Marrow and PBMC Populations

The selection of antigen-specific V_(H) sequences from each animal was based on both abundance in bone marrow and a filter for an adjustable threshold abundance in total PBMCs. The more stringent filter scores antigen-specific V genes as positive if they are represented among the top 10 most abundant in the bone marrow and among the top 50 most abundant among peripheral blood monocytes. Table 29 below lists the abundance ranking and frequency (as % of the total repertoire for V genes from different animals).

TABLE 29 Examples of V_(H) sequence frequencies and rankings in terms of abundance^(a) used in the filtering analysis. SEQ ID % total rank % total rank CDRH3 NO:  BM total BM PBMC PBMC Goat 52 VRCYTHWSDNNGRCYGPMY 320 0.31 2 0.07 31 GRDGYYSDYYAVDV 321 0.24 4 0.12 6 ADGYSYPNAY 322 0.22 6 0.12 9 GRDV 323 0.20 8 0.11 11 ARGYSDYAYFYGGAIEV 324 0.17 9 0.07 25 GKGVYYNYGADVED 325 0.17 10 0.06 41 ARDTSIDYAYRYNYEIDY 326 0.16 11 0.08 19 ARGISDWDYGLVGLNV 327 0.13 18 0.06 57 ARSNGGGIGDVDI 328 0.13 19 0.09 13 VTGGNGYGYDAPF 329 0.12 23 0.06 46 ARDKEWPGASSIDY 330 0.12 24 0.06 47 ISGRSGVGDDWAAHY 331 0.12 25 0.09 14 VGGSGYNYRYVYDGVDI 332 0.12 28 0.08 18 ARDRTCCGAGYGSRPDIEV 333 0.11 29 0.10 12 ARVYADDTYDYEDAFDY 334 0.11 30 0.07 27 ARGRYSGYGYGYGYDQYYIDY 335 0.10 34 0.06 55 ARSNGGGIGDVDV 336 0.10 36 0.17 4 TSCYSVYGYNCADRDYGANF 337 0.10 38 0.06 42 Sheep 54 ARGPDYSTYGTAYIYYLDY 338 0.40 1 0.13 43 ARGPDYSTYGSYYLYYLDY 339 0.38 2 0.18 22 ARGGGDY 340 0.35 3 0.19 18 ASSILAISNY 341 0.35 4 0.77 1 ARCHYGGHCETYGLPMDY 342 0.32 5 0.12 48 VRDYEEYNHAYAYGGY 343 0.29 6 0.24 12 ECYNGYGYAYGYNIDT 344 0.27 7 0.26 10 GREGNIAYGYDYGPHNIDY 345 0.24 8 0.30 8 VTGNMYSCDVDF 346 0.21 13 0.47 4 ATSACGYTHCIDY 347 0.21 14 0.53 2 AGSIRWFDRPTSGV 348 0.21 15 0.12 47 VRVRRGYGHAYGYNDY 349 0.21 16 0.34 7 VRGYYSPPGYDICFDD 350 0.18 20 0.15 34 ARGLMPIFDR 351 0.18 19 0.45 5 ARGIGIPRLDY 352 0.17 23 0.13 40 TRNDIGYSYLPDY 353 0.17 25 0.10 73 VRDYYGGVGVAVSGDY 354 0.17 22 0.25 11 ARGLYDVSI 355 0.17 24 0.17 28 ARAAGFTRAAADVDY 356 0.16 26 0.10 64 ARGFYSTNSVARYYADY 357 0.15 30 0.17 23 VRDDGTIGYAGSIDY 358 0.14 32 0.13 46 GRESRSVSGYGHGVTNFDF 359 0.13 37 0.27 9 VSLSTLCDAAGAFYGEY 360 0.13 40 0.14 35 ARYSDFGSAGNYLDY 361 0.13 41 0.17 24 rank % total rank CDRH3 % BMPC BMPC PBMC PBMC ARDMDGGNVGYGM 362 0.88 2 0.10 95 ARADRGFYAGTSDYTGYNL 363 0.60 4 0.14 45 ARADRGFYAGTSDYSGYNL 364 0.51 5 0.24 7 ARGSGWYGGLNL 365 0.40 9 0.20 20 ASNYADPPGYNYTPFNL 366 0.35 10 0.09 129 ARLYAGSSYSISPDYGMDL 367 0.30 12 0.07 203 ARDSYVGDEITTGYSFNL 368 0.21 24 0.12 66 ARNYAGYGGYVYLSEYHFNL 369 0.19 27 0.13 54 ASNYADGPGYGFAPFNL 370 0.19 28 0.20 15 ARDYYSSGWGGFNL 371 0.19 30 0.06 277 ARLNIGGADGL 372 0.17 36 0.06 291 ARDYGSSGWGGFNL 373 0.15 52 0.19 24 ASNYAGDAGYGYAPFNL 374 0.14 59 0.20 22 ARDLGAAEYGYGSPFNL 375 0.13 60 0.17 31 ASSHLSDDYYFNL 376 0.12 69 0.06 301 ARGLVMLVMSILPDL 377 0.12 70 0.14 43 ATYTYDYAGYSHAGFNL 378 0.12 77 0.14 44 ARDPPGYGINFVAMDL 379 0.11 78 0.06 224 AREFAAGSFNF 380 0.11 85 0.18 26 Rabbit CCH2 ATDRGPSGSGPLDL 381 0.71 1 0.10 89 SRDGKYAGIAGYGSTYFDL 382 0.67 2 0.06 195 AGDGRSYYADYAFVDL 383 0.56 3 0.23 23 ARDPVTRLVAGADYFDL 384 0.48 4 0.08 122 ARDVYTYDADGDYRHFNL 385 0.47 5 0.06 189 ARAPVYYNGGYAGFREFNL 386 0.46 6 0.12 59 ARVGNHYGMDL 387 0.45 9 0.08 127 ARGAAGYAGYAYAYYYFDF 388 0.44 10 0.10 87 ARDPVNRLQAGADYFNL 389 0.44 11 0.20 30 ARDFSYGYAGQAYVTPFIL 390 0.40 12 0.10 84 ARQPYTGTTL 391 0.36 16 0.07 159 VRDSFLDYGDFGL 392 0.34 17 0.13 55 ARGGGRGELNL 393 0.34 19 0.06 209 ARDFGASSYYLFDL 394 0.32 22 0.05 226 ARGVIYDDFGDYPYYLDL 395 0.31 25 0.11 69 ARDLDGYGDFIYFGL 396 0.30 27 0.11 68 AKYDDYAHYFHL 397 0.30 28 0.10 82 ARDGFPCASDYYRACLDL 398 0.29 29 0.10 85 ARTLIYASRPNYFDL 399 0.28 32 0.11 72 ARDGDGGSFGYTL 400 0.27 34 0.09 100 ARDFNL 401 0.27 36 0.36 14 ATNVGGGYVARLDL 402 0.26 37 0.07 178 ARDMLVVVGLNL 403 0.25 39 0.08 132 AKYNYDDYGDQYYFNL 404 0.24 42 0.05 223 ARDYNL 405 0.18 63 0.10 86 AGRSGWDGFNL 406 0.16 73 0.06 182 TREFAYAYSSGYYGFNL 407 0.16 75 0.05 245 ARYNYDDYGDQYYFNL 408 0.14 94 0.05 241 ASYGGGSFISPDYLNL 409 0.14 97 0.08 141 ARGNYDDYGAEYFGL 410 0.12 106 0.06 192 TRGGSYTDGDVGAVYATDFNL 411 0.12 121 0.08 142 ARDLGDTYYSGALWYWNL 412 0.12 125 0.09 93 ARFAYSYGYAGNIDYYGMDL 413 0.11 129 0.06 208 ARVDLAYYNGGDTTTPYATEFTL 414 0.11 132 0.06 214 ARGTYTYDDYGDYRAFDP 415 0.11 138 0.09 97 ^(a)The abundance threshold can be modified for stringency to optimize the isolation of antigen-specific V_(H) sequences. The inventors chose 0.05 - 0.1% cutoffs for PBMC frequency and have shown the top bone marrow sequences passing this threshold.

Selecting V_(L) Sequences by Abundance in Bone Marrow

The selection of antigen-specific V_(L) sequences relies upon abundance data in bone marrow. As with V_(H), the V_(L) sequences were also amplified via 5′ RACE using constant region primers.

TABLE 30 Top V_(L) sequences by abundance in bone marrow plasma cells SEQ ID CDRL3 Percent NO:  Rabbit CCH1 QGYSSYPLT 0.85 416 QCTRYDRSDGGA 0.78 417 QSAYFSVTGDSYA 0.56 418 QSAYDASTYVPSA 0.53 419 QTAYGSSSSDNV 0.52 420 LGGYSGSADLT 0.51 421 AGGYSSSSDNA 0.41 422 GGDLGGGMDA 0.39 423 LGGYSSSTGTT 0.38 424 LGGYSYGSNT 0.35 425 Rabbit CCH2 QQGYSTPLT 2.42 426 QGYRRYPHT 1.20 427 LGGDTSRTGLT 1.05 428 LGGVSGSADFVS 0.77 429 QSAYYSSNPDIT 0.63 430 LGGVSGSADFLS 0.58 431 QSADYTTFTDSHA 0.55 432 QSAYYGSSGKIT 0.54 433 QSAYYSSSADNA 0.53 434 QSYYYDSIPYNV 0.51 435 Rabbit HEL1 LGGYISASDNG 2.12 436 AGAYTTSVSDAVRA 2.12 437 QGGYDCSSADCHV 0.90 438 LGGYNYDGTGRT 0.67 439 QGYSNYHLT 0.67 440 QGGYSGNIYD 0.57 441 QGYWHDGIWA 0.56 442 LGVGTYINGDGRGV 0.49 443 LGSYDCDRADCTA 0.48 444 QFTHSSSNSDGNP 0.45 445 Rabbit HEL2 QSYVYGADTPA 2.38 446 QCSFVTNGDNSHNT 1.40 447 QSYYGVASKHA 0.92 448 QQEYESRDVPNP 0.40 449 QQSYTRHNAENI 0.35 450 QTSNAITTYGAA 0.35 451 LGVDTDINGDTTWA 0.34 452 QCTSYGSTYVGP 0.33 453 AGDFGASIVA 0.31 454 QSYDYSSSSTYVNI 0.27 455 Goat 52 YDSSSSGV 0.76 456 FDSSSNYI 0.42 457 YDSTYGGSI 0.39 458 FSTDYIDV 0.39 459 YDSSSTGV 0.37 460 TDSNNNAV 0.37 461 YSSSNYGV 0.36 462 YDSDSSYI 0.35 463 YQSDWSLL 0.35 464 IQSDWTGV 0.32 465 Sheep 54 YDSSSYTV 0.80 466 YRSPYTGV 0.77 467 YKSGGIV 0.45 468 YDNNNSNL 0.43 469 DDTSDSL 0.39 470 YRSPGTVV 0.38 471 YKTPYTGV 0.37 472 YDSSSYGV 0.32 473 YKSGGTGV 0.31 474 YDSGSYGV 0.31 475

Example 13 ELISA Screening of Selected Highly Abundant V_(H) and V_(L) Synthetic Genes by Combinatorial Pairing

The lower polarity of the rabbit, sheep, and goat V_(H) and V_(L) repertoires (as compared to murine V_(H) and V_(L) repertoires in Example 9) necessitates a modified approach to identify high affinity pairings of antigen-specific V_(H) and V_(L). The use of ELISA screening of small combinatorial panels of different synthetic V_(H) and V_(L) pairings avoids the difficulty of manually pairing the synthetic V_(H) and V_(L) based solely on rank, as was done for the higher polarity murine repertoires.

Isolation of Antigen-Specific Antibodies.

Synthetic genes of highly abundant V_(H) and V_(L) sequences from sheep 54 were made as described in Example 9. The V_(H) and V_(L) genes were separately synthesized for cloning as Fab constructs, with Nco I/Not I sites appended onto the V_(L) and Nhe I/Hind III sites appended onto the V_(H). This facilitates cloning of the synthetic genes into the pFab-S vector, a pMAZ360-based vector (Mazor et al., 2007) engineered for expression as soluble Fab in the periplasm of E. coli. In addition, the synthetic genes were subsequently amplified as scFvs with a glycine-serine linker (GGGGS)₄ (SEQ ID NO:806) (as in Example 9) between the V_(L) and V_(H) sequences constructed using overlap extension PCR. For scFv cloning, Sfi I restriction endonuclease sites were added flanking each V_(H)-linker-V_(L) gene sequence to facilitate cloning of the synthetic gene constructs into compatible pMoPac16 vectors (Hayhurst et al., 2003). Expression and ELISA screening from E. coli lysates is accomplished as described in Example 9. Table 31 lists the sheep 54 V_(H) and V_(L) CDR3 sequences used to construct FAbs and scFvs and their relative abundance in the bone marrow and in PBMCs. Table 32 lists the full amino acid sequences of the 7 V_(H) and 5 V_(L) synthetic genes from sheep 54. The most abundant somatic variant of each CDRH3 was selected unless otherwise indicated. For the V_(L), the amino acid consensus sequence of the CDRL3 group was synthesized.

TABLE 31 Sheep 54 V_(H) and V_(L) synthetic genes SEQ ID % Bone % rank CDRH3 NO:  marrow PBMC PBMC ARGPDYSTYGTAYIYYLDY 476 0.40 0.13 43 ARGPDYSTYGSYYLYYLDY 477 0.38 0.18 22 ARGGGDY 478 0.35 0.19 18 ASSILAISNY 479 0.35 0.77 1 ARCHYGGHCETYGLPMDY 480 0.32 0.12 48 VRDYEEYNHAYAYGGY 481 0.29 0.24 12 ECYNGYGYAYGYNIDT 482 0.27 0.26 10 % Bone CDRL3 marrow^(a) YDSSSYTV 483 0.80 YRSPYTGV 484 0.77 YKSGGIV 485 0.45 YDNNNSNL 486 0.43 DDTSDSVL 487 0.39 ^(a)For CDRL3, percentages were based on PC-V repertoire for sheep 54 sorted using the 281-2 +60-CD138 antibody.

TABLE 32 Sheep 54 V_(H) and V_(L) synthetic genes - full amino acid sequences and the corresponding CDR3 sequences (also listed in Table 1 above) CDRH3 Full amino acid sequence ASSILAISNY (SEQ ID QVRLQESGPSLVKPSQTLSLTCTVSRFSLTNYGVGWVRQAP NO: 488) GKALEWLGGIDKDGDTGYNPALKSRLSITRDTSKSQVSLSLS STTTEDTAVYYCASSILAISNYWGPGVLVTVSS (SEQ ID NO: 489) VRDYEEYNHAYAYGGY QVQLQESGPSLVKPSQTLSLTCTVSGFSLKTHGVGWVRQAP (SEQ ID NO: 490) GKALESVGIIFTGGGTGYNPALKSRLSITRDTSKSQVSLSLSS VTTEDTAVYYCVRDYEEYNHAYAYGGYWGPGLLVTVSS (SEQ ID NO: 491) ARGPDYSTYGSYYLYYL QVQLQESGPSLVKPSQTLSLACTVSVFSLTSYTVGWVRQAP DY^(a)(SEQ ID NO: 492) GKAPEWVGSIGGSGRRVYNPALKSRVSIARDTSKNQVSLSL SSVTTEDTAVYYCARGPDYSTYGSYYLYYLDYWGPGLLVT VSS (SEQ ID NO: 493) ARGPDYSTYGTAYIYYLD QVQLQESGPSLVKPSQTLSLACTVSVFSLNSYTVGWVRQAP Y (SEQ ID NO: 494) GKALEWVGSIGGSGRRVYNPALKSRVSIARDTSKSQVSLSLS SVTAEDTAVYYCARGPDYSTYGTAYIYYLDYVGPRTPGHRL L (SEQ ID NO: 495) ARCHYGGHCETYGLPMD QVRLQESGPSLVKPSQTLSLTCTVSGFPLTSNAVGWVRQAP Y (SEQ ID NO: 496) GKVPEWLGGISTRGSTYYNSALKSRLSITRDTSKSQVSLFLSS VTTEDTALYYCARCHYGGHCETYGLPMDYWGPGLLVTVSS (SEQ ID NO: 497) ARGGGDY (SEQ ID QVQLQESGPSLVKPSQTLSLTCTISGFSLTDHDVEWVRQAPG NO: 498) KALEWVGAIYDSGNAYYNPALKSRLSITRDTSRSRVSLSLSN VTTEDTALYYCARGGGDYWGPGLLVTVSS (SEQ ID NO: 499) ECYNGYGYAYGYNIDT QVQLQESGPSLVKPSQTLSLTCTVSGFSLTRYGVGWVRQAP (SEQ ID NO: 500) GKALEWVGYIYSDGGIYYNPALKSRLSITRDTSKSQVSLSLS SVTTEDTAVYYCECYNGYGYAYGYNIDTWGPGLLVTVSS (SEQ ID NO: 501) CDRL3 Full amino acid sequence YDSSSYTV (SEQ ID QAVLTQPSSVSRSLGQSVSITCSGSSSNVGYGSYVGWFQQVP NO: 502) GSAPKLLIYGATSRASGVPDRFSGSRSGNTATLTITSLQAEDE ADYYCASYDSSSYTVFGSGTRLTVL (SEQ ID NO: 503) YRSPYTGV (SEQ ID QSALTQPASVSGNPGQTVTISCTGTNSDIGAANYIGWYQQLP NO: 504) GSAPKTLIYAVDKRPSGIPARFSGSKSGNTATLTISGLQAEDE ADYYCSSYRSPYTGVFGSGTRLTVL (SEQ ID NO: 505) YKSGGIV (SEQ ID QSALTQPASVSGNPGQTVTISCTGTSSDVGIYKYVGWYQQL NO: 506) PGSAPKTLIYHVNERPSGIPARFSGSKSGNTATLTISGLQAED EADYYCSSYKSGGIVFGSGTRLTVL (SEQ ID NO: 507) YDNNNSNL (SEQ ID QTVLTQPSSVSKSLGQAVSITCSGSSSNIGYGDYVRWFQQVP NO: 508) GSAPKLLIYGASSRASGVPDRFSGSRSGNTATLTISSLQAEDE ADYYCATYDNNNSNLFGSGTRLTVL (SEQ ID NO: 509) DDTSDSVL (SEQ ID QAVLTQPSSVSKSLGQSVSITCSGSSSNVGYGDYVSWFQQV NO: 510) PGSAPKLLIYGATRRASGVPDRFSGSRSGNTATMTISSLQAE DEADYYCASDDTSDSVLFGSGTRLTVL (SEQ ID NO: 511) ^(a)For this V_(H), the second most abundant somatic variant was synthesized.

Example 14 Immunoinformatic Mining of Lymphoid Repertoires Via Clustering Analysis of High Resolution V Gene DNA Sequence Data Sets

The V immunoglobulin cDNA repertoires from bone marrow in sheep, goats and to a lesser extent rabbits are less polarized than those of mice. This example describes a bioinformatics approach for identifying antigen-specific VH and VL genes and then pairing hem to produce desired, high affinity antibodies.

The inventors discovered that phylogenetic analysis (more specifically clustering analysis) can be used to help identify desired antigen-specific V genes. The high resolution provided by high sample sizes can aid in identifying antigen-specific monoclonal antibodies that will have resulted from high levels of somatic hypermutation during the affinity maturation process. Therefore, by identifying clusters of highly related sequences (somatic variants arising from a clonal expansion), an additional filter emerges for identifying antibodies arising as a result of a recent clonal expansion which occurred after immunization. Highly related sequences can be somatic variants within a single CDR3 group or somatic variants of the CDR3 group (e.g. somatic hypermutation within the CDR3 itself). By identifying clusters of highly related sequences within multiple lymphoid populations (bone marrow, spleen, lymph nodes, and PBMCs), a clear picture of recent clonal expansion and affinity maturation emerges. These events indicate a recent antigen-specific response and can aid in isolation of monoclonal antibody sequences, especially in instances where repertoire polarity is low.

Repertoire Clustering Using Multiple Sequence Alignment and Phylogenetic Analysis.

There are numerous computer programs available for multiple sequence alignment, but most are limited in the size of the data set that can be aligned. MUSCLE or Multiple Sequence Comparison by Log Expectation (Edgar, 2004) is ideally suited for extremely large data sets and was chosen to align the V_(H) and V_(L) repertoires, which often have upward of several thousand unique amino acid sequences depending on the read numbers vailable. The raw 454 sequencing data was processed as described in Example 9 to produce amino acid sequences aligned via homology-driven motif searches. To ensure only near full-length V_(H) and V_(L) sequences were analyzed, a series of filters were applied that removed highly truncated sequences and those containing stop codons. For example, the V_(H) filter included the following criterion: 1) full length ≧100 residues, 2) FR4 length >2 residues, 3) sequences containing no stop codons, and 4) unique sequences (as defined from CDR1 to CDR3) with at least 2 reads (removes unique sequencing errors). Application of this filter to the rabbit CCH1 V_(H) aligned PC-V data set (>30,000 identified VH amino acid sequences) limited the data to ˜5000 unique amino acid sequences. These 5000 amino acid sequences were annotated by abundance (e.g. most abundant unique amino acid sequences named 1) in FASTA format and aligned with MUSCLE using default parameters for gap opening and gap extension penalties and the default scoring matrix. The alignment produced by MUSCLE was then processed by tree building software to cluster sequences. In ClustalX, a Phylip tree file was created using the Neighbor-Joining method. The tree file was then analyzed and manipulated using Dendroscope (Huson, 2007). In Dendroscope, it is easy to search the tree and quickly identify those annotated highly abundant sequences that are also located in highly branched limbs of the tree. The software is also very interactive in that you can then select large clusters of sequences and export for examination of the annotated data in Microsoft Excel. Table 33 shows a cluster of V_(H) sequences identified from rabbit CCH1 PBMC using clustering analysis as described above. Table 34 provides CDRH3 abundances in PC-V (from bone marrow) and tLT-V (from PBMC) data compared by color coding to show somatic variants for the cluster identified in both bone marrow and blood populations. Large related cluster of sequences with similar CDRH3 sequence are found both in PBMC and BMPC populations. Representative CDRH3s that are very abundant are shown. Clustering analysis also identifies large clusters of sequences that are moderately abundant (with regards to representative CDRH3 groups), but again likely arise from antigen-specific clonal expansion.

TABLE 33 Cluster of unique highly related PBMC somatic variants identified by clustering analysis PBMC Rank (by full SEQ ID sequence) CDRH3 group NO:  # SM^(a) 92 NYAGHPGYGYAPFNL 512 16 782 NYAGHSGYGYAPFNL 513 17 1430 NYAGHPGYGYAPFNL 514 17 303 NYAGHPGYGYAPFNL 515 17 1429 NYAGHPGYGYAPFNL 516 17 2158 NYAGHPGYGYAPFNL 517 7 1106 NYADGPGYGFAPFNL 518 10 2029 NYADGPGYGFAPFNL 519 9 169 NYADGPGYGFAPFNL 520 12 1887 NYADGPGYGFAPFNL 521 12 240 NYADGPGYGFAPFNL 522 11 1891 NYADGPGYGFAPFNL 523 12 356 NYADGPGYGFAPFNL 524 13 61 NYAGGPGYGFAPFNL 525 8 2515 NYAGGPGYGFAPFNL 526 9 6 NYAGNPGYGYAPFNL 527 13 2662 NYAGNPGYGYAPFNL 528 14 2764 NYAGNPGYGYAPFNL 529 14 2770 NYAGNPGYGYAPFNL 530 17 2234 NYAPFPGYGFAPFNL 531 11 203 NYAGDAGYGYAPFNL 532 14 2744 NYAADAGYGYAPFNL 533 13 2745 NYAADAGYGYAPFNL 534 12 417 NYAADAGYGYAPFNL 535 10 1075 NYAGDAGYGYAPFNL 536 9 104 NYAADAGYGYAPFNL 537 9 382 NYAADAGYGYAPFNL 538 9 1076 NYAGDAGYGYAPFNL 539 9 1072 NYAGNAGYGYAPFNL 540 13 143 NYADAGYGYAPFNL 541 14 2591 NYAGDAGYGYAPFNL 542 13 764 NADGNGGYRYAPFNL 543 15 1071

544 9 2236

545 10 ^(a)#SM is the number of somatic mutations as determined by germline alignment using IMGT HighV-Quest. Each listed CDRH3 represents a unique somatic variant. Some somatic variants have the same number of somatic mutations, but are different unique sequences.

TABLE 34 CDRH3 abundance in CCH1 PBMC and BMPC sorted by percent PBMC (top) and percent BMPC (bottom). Color coded to match Table 1. % % SEQ CDRH3 PBMC BMPC ID NO:  YDGSIAYLAL 1.44 0.02 546 YSASSGAYYDGYYFNL 0.78 #N/A 547 ASSSSGHYYDGYYFNL 0.63 0.00 548 DLVMLSYL 0.28 0.01 549 GGYSTFDL 0.28 0.04 550 NYAGNPGYGYAPFNL 0.27 0.06 551 HRHGDAYPNL 0.24 0.06 552 NFKL 0.24 0.04 553 GDDDYWYYLNL 0.23 #N/A 554 ADRGFYAGTSDYSGYNL 0.23 0.47 555 DYDL 0.23 0.02 556 NYADGPGYGFAPFNL 0.22 0.18 557 DSPTSGYYGGYYFDL 0.22 0.01 558 EIWSDGYYDL 0.21 0.03 559 EAESGNSYADFNL 0.21 0.02 560 NYAADAGYGYAPFNL 0.20 0.03 561 GIFDYNVDGAETL 0.20 #N/A 562 DYGSSGWGGFNL 0.20 0.14 563 DWSADIDYILTL 0.20 0.04 564 NYAGDAGYGYAPFNL 0.19 0.14 565 DMDGGNVGYGM 0.87 0.13 566 GLNAAGYTTFAYGTTVMDL 0.84 0.01 567 FDAAYADFGVANL 0.60 #N/A 568 ADRGFYAGTSDYTGYNL 0.55 0.13 569 ADRGFYAGTSDYSGYNL 0.47 0.23 570 DAGGSYSYYFDL 0.42 0.04 571 DAGGYTGDGYYFKL 0.40 0.03 572 GGPIHYSNL 0.39 0.02 573 GSGWYGGLNL 0.35 0.19 574

0.33 0.09 575 LYAGSSYSISPDYGMDL 0.31 0.06 576

Example 15 Proteomic Identification and Quantization of Antibodies in Rabbits and Other Mammals

Rabbit serum Ig proteins from immunized animals as described in Example 6 were isolated by affinity chromatography using protein A beads with elution using glycine buffer, pH 2.5. Following elution, Ig protein solution was buffer exchanged to Phosphate Buffer Saline.

Protein A-purified serum IgG proteins were isolated from traces of rabbit serum albumin (RSA) that co-eluted with antibodies using size exclusion chromatography (SEC). SEC was carried out with Na-acetate, pH 5.0, as the mobile phase and TSKgel G3000SWx1 column as the stationary phase (Tosoh Bioscience LLC). Samples were subsequent digested with immobilized papain (Pierce) to produce two FAB fragments and an Fc domain per IgG molecule. FAB fragments were isolated from the Fc fragments by applying the digestion solution to a protein A affinity column with elution as above. FAB fragments were collected in the flow through and washing steps.

Purified FAB fragments were denatured in freshly prepared 8M Urea solution pH 8.0 in 100 mM Sodium carbonate pH 10. A mixture of 97.5% v/v acetonitrile, 2% v/v Iodoethanol, 0.5% v/v Triethylphosphine was added to reduce and alkylate Fab fragments, and samples were incubated at 60° C. for 60 min. Samples were then lyophilized using speedvac centrifugation and resuspended to final concentration of 2M Urea. Samples were then subjected to protease digestion by trypsin. Proteolytic cleavage was accomplished using sequencing grade trypsin (Sigma) at 37° C. for 5 hr with the trypsin:protein ration of 1:50. Digestions were quenched with 1% formic acid. To remove contaminants, peptides were bound and washed on C-18 Hypersep SpinTips (Thermo Scientific) and filtered through 10 kDa Microcon YM-10 centrifugal filters (Amicon) prior to LC-MS/MS analysis.

Peptides were then separated on a reverse phase Zorbax C-18 column (Agilent) with a gradient from 5% to 38% acetonitrile, 0.1% formic acid over 230 mins. Peptides were eluted directly into an LTQ-Orbitrap mass spectrometer (Thermo Scientific) by nano-electrospray ionization. Data-dependant ion selection was enabled, with parent ion mass spectra (MS1) collected at 100K resolution. Ions with known charge >+1 were selected for CID fragmentation spectral analysis (MS2) in order of decreasing intensity, with a maximum of 12 parent ions selected per MS1 cycle. Dynamic exclusion was activated, with ions selected for MS2 twice within 30 sec. excluded from MS2 selection for 30 sec.

Ions identified in an LC-MS/MS run as corresponding to peptides from the constant regions of the heavy and light chains were excluded from data-dependant selection in subsequent experiments in order to increase selection of peptides from the CDR3 region. Moreover, in addition to the full range of m/z peptides, gas fractionation was carried out to lower ion separation of dominant peptides in the sample. Gas fractionation was with m/z of i) 300-800, ii) 800-900 and iii) 900-1500. This procedure improve the peptide coverage.

LC-MS/MS data were searched against database containing full V genes sequences obtained by NextGen sequencing of the V gene repertoires as described in Example 6 using the Sequest search algorithm as part of the Bioworks software package (Thermo Scientific). Filters were applied to ensure high confidence peptide identifications as follows: ΔCN ≧0.250; XCorr=2.0, 2.5, and 3.0 for +2, +3, and ≧+4 charge; and accuracy ≦10.0 ppm. Alternatively, other label-free (Silva et al., 2006b; Gygi et al., 1999; Ross et al., 2004) or isotope label-based quantitative methods for mass spectrometry could be used to determine the abundancy of specific CDR3 families at the protein level.

Table 35 shows a comparison of V,D and J family abundance from 454 sequencing cDNA V gene abundance data (i.e., transcriptional abundance) and shotgun MS proteomic data (Table 35). The transcriptional profile correlates with the proteomic data, reported as peptide counts.

TABLE 35 Abundance of, D and J family from transcription data and MS data mRNA seq MS Peptide Family counts count F_4 (J) 987 264 F_2 (J) 199 63 F_3 (J) 87 38 F_6 (J) 11 12 F_5 (J) 8 4 8_1 (D) 92 408 6_1 (D) 80 120 2_1 (D) 49 217 1_1 (D) 45 190 4_2 (D) 31 77 7_1 (D) 10 34 4_1 (D) 5 19 5_1 (D) 2 5 3_3 (D) 1 6 3_1 (D) 0 0 1S40 (V) 110 348 1S45 (V) 102 420 1S47 (V) 99 167 1S7 (V) 44 244 1S21 (V) 10 29 1S29 (V) 9 5

In some embodiments, grouping of V genes based on CDR3 families substantially improves quantitation of the peptide dataset. Sample-specific protein sequence databases were created from the high-throughput V gene cDNA sequencing data. The sequence database was created by grouping of V genes based on CDR3 families substantially improves quantitation of the peptide dataset. This introduced a number of additional steps into the bioinformatics analysis pipeline: (1) After performing the shotgun proteomics experiments and identifying peptides based on the standard mass spectrometry analysis pipeline and the sample-specific sequence database, peptides that overlap CDR3 regions were identified. (2) These observed peptides were mapped to V gene cDNA-defined CDR3 families, and (3) Spectral counts attributable to each CDR3 family were defined.

CDR3 regions of the V gene and MS data were concatenated to the FR4 and the N-terminal of CH1 region. LC-MS/MS data were searched in this case against this database containing grouped CDR3 sequence using the Sequest search algorithm as part of the Bioworks software package (Thermo Scientific). Filters were applied to ensure high confidence peptide identifications as mentioned above.

Total count of peptides identified in FABs that were isolated from Concholepas concholepas hemocyanin (CCH) immunized rabbit CCH1 were compared to the VH cDNA repertoire data which reflects the transcript abundance of the respective V genes. In cases where peptides identified fit uniquely to the CDR3 from sequencing data (Table 36 italicized text) the corresponding CDR3 from the transcript sequence are shown. In the case where the peptide identified consists trypsin digestion site in the CDR3 region, no unique corresponding CDR3 from sequencing data is shown (since that CDR3 fragments corresponds to multiple sequences). These arise because the presence of Lys or Arg amino acids in the CDR3 region results in short peptides following trypsin digestion (Table 36, bolded text). As expected, the most abundance peptide identified in this example did not correlate with the most abundant VH gene transcript expressed by bone marrow cells because the latter reflects only a snapshot of transcription and protein synthesis. However, antibodies persist in circulation with a t1/2 of approx 14 days for IgGs. Putative antibodies originating from “declining” plasma cells that show moderate transcription levels but are nonetheless highly represented in the MS peptide counts are marked by underlining in Table 36.

TABLE 36 Example of CDR3 VH gene sequence abundance (frequency ranking) determined by NextGen seuencing of the total bone marrow repertoire and the corresponding abundance of the respective antibodies in serum as deduced from counting the CDR3 peptide identified by MS. SEQ mRNA SEQ mRNA CDR3 ID seq ID Peptide Sequences NO: counts MS CDR3 peptides NO: counts ARRADGGTYNLWGPGT 577 29 RADGGTYNLWGP 578 23 LVTVSSGQPK GTLVTVSSGQPK ARLNIGGADGLWGPGT 579 24 LNIGGADGLWGP 580 15 LVTVSSGQPK GTLVTVSSGQPK ARGYNTFDPWGPGTLV 581 10 GYNTFDPWGPGTL 582 8 SVSSGQPK VSVSSGQPK ARNFKLWGPGTLVTVS 583 15 NFKLWGPGTLVTV 584 8 SGQPK SSGQPK ARNVYGASRVCGMDL 585 12 VCGMDLWGPGTL 586 8 WGPGTLVTVSSGQPK VTVSSGQPK RRSGLWGPGTLVAVSS 587 35 SGLWGPGTLVAVS 588 7 GQPK SGQPK ARSSYVNSGGAANLWG 589 13 SSYVNSGGAANLW 590 7 PGTLVTVSSGQPK GPGTLVTVSSGQP K ARGGYGGYGYDRAFDF 591 11 AFDFWGPGTLVTV 592 7 WGPGTLVTVSSGQPK SSGQPK ARSPSSGSSNLWGPGTL 593 5 SPSSGSSNLWGPG 594 6 VTVSSGQPK TLVTVSSGQPK ARNFGLWGQGTLVTVS 595 21 NFGLWGQGTLVTV 596 6 SGQPK SSGQPK ARNFGLGGQGTLVTVS 597 8 NFGLGGQGTLVTV 598 6 SGQPK SSGQPK ARGGGSDGDGYNLWG 599 10 GGGSDGDGYNLW 600 4 PGTLVTVSSGQPK GPGTLVTVSSGQP K ARNYGLWGPGTLVTVS 601 6 NYGLWGPGTLVTV 602 4 SGQPK SSGQPK VRNLYLWGPGTLVTVSS 603 3 NLYLWGPGTLVTV 604 4 GQPK SSGQPK ARVVPGVHSFNLWGPG 605 3 VVPGVHSFNLWGP 606 4 TLVTVSSGQPK GTLVTVSSGQPK ARGGNPNYDYGLWGP 607 2 GGNPNYDYGLWG 608 4 GTLVTVSSGQPK PGTLVTVSSGQPK ARGLFGRAFPFKLWGP 609 6 AFPFKLWGPGTLV 610 4 GTLVTVSSGQPK TVSSGQPK ARDLYGGSSDLWGPGT 611 23 DLYGGSSDLWGPG 612 3 LVTVSSGQPK TLVTVSSGQPK AREGLYNLWGPGTLVT 613 3 EGLYNLWGPGTLV 614 3 VSSGQPK TVSSGQPK ARGAGGSGYNLWGPG 615 11 GAGGSGYNLWGP 616 3 TLVTVSSGQPK GTLVTVSSGQPK SRGGGAGYGLWGPGT 617 17 GGGAGYGLWGPG 618 3 LVTVSSGQPK TLVTVSSGQPK ARKDTNPHWGLWGPG 619 25 DTNPHWGLWGPG 620 3 TLVTVSSGQPK TLVTVSSGQPK ARKDSNPHWGLWGPG 621 64 KDSNPHWGLWGP 622 3 TLVTVSSGQPK GTLVTVSSGQPK ARGAGGSGYGLWGPG 623 6 GAGGSGYGLWGP 624 3 TLVTVSSGQPK GTLVTVSSGQPK ARDDVGDGAFVHNLW 625 25 DDVGDGAFVHNL 626 3 GPGTLVTVSSGQPK WGPGTLVTVSSGQ PK ARDHSGNSGWHPDLW 627 10 DHSGNSGWHPDL 628 2 GPGTLVTVSSGQPK WGPGTLVTVSSGQ PK ARYYSGTGSDLWGPGT 629 3 YYSGTGSDLWGPG 630 2 LVTVSSGQPK TLVTVSSGQPK ARGVGGYGSDLWGPG 631 15 GVGGYGSDLWGP 632 2 TLVTVSSGQPK GTLVTVSSGQPK ARGNTYAVDGYNLWGP 633 24 GNTYAVDGYNLW 634 2 GTLVTVSSGQPK GPGTLVTVSSGQP K ARETAGDKNWLFHLW 635 13 NWLFHLWGPGTL 636 2 GPGTLVTVSSGQPK VTVSSGQPK AREGYGGYVGYMGLW 637 9 EGYGGYVGYMGL 638 2 GPGTLVTVSSGQPK WGPGTLVTVSSGQ PK ARVVDDGDGCDLWGP 639 5 VVDDGDGCDLWG 640 2 GTLVTVSSGQPK PGTLVTVSSGQPK LRERSGVNTDLWGPGT 641 25 SGVNTDLWGPGTL 642 2 LVTVSSGQPK VTVSSGQPK AREALYNLWGPGTLVT 643 6 EALYNLWGPGTLV 644 2 VASGQPK TVASGQPK ARGAGGSGYDLWGPG 645 3 GAGGSGYDLWGP 646 2 TLVTVSSGQPK GTLVTVSSGQPK ARGAYGNTNTYYNLGG 647 4 GAYGNTNTYYNLG 648 1 PGTLVTVSSGQPK GPGTLVTVSSGQP K ARWAGSNGFSLWSPGT 649 4 WAGSNGFSLWSPG 650 1 LVTVSSGQPK TLVTVSSGQPK LRERSGVNTDLGAPGT 651 2 SGVNTDLGAPGTL 652 1 LVTVSSGQPK VTVSSGQPK ARNLGITNDNNLWGPG 653 21 NLGITNDNNLWGP 654 1 TLVTVSSGQPK GTLVTVSSGQPK ARGAGWVDYSLWGPG 655 30 GAGWVDYSLWGP 656 1 TLVTVSSGQPK GTLVTVSSGQPK VRDTIGLWGPGTLVTVS 657 7 DTIGLWGPGTLVT 658 1 SGQPK VSSGQPK ARGGNPNYDYGLGGP 659 7 GGNPNYDYGLGG 660 1 GTLVTVSSGQPK PGTLVTVSSGQPK AREFWASTTILWGPGTL 661 69 EFWASTTILWGPG 662 1 VTVSSGQPK TLVTVSSGQPK AREFGRSRNLWGPGTL 663 2 EFGRSRNLWGPGT 664 1 VTVSSGQPK LVTVSSGQPK LDLWGQGTLVT 665 96 VSSGQPK FNLWGPGTLVT 666 53 VSSGQPK AFDPWGPGTLV 667 36 TVSSGQPK FIDLWGPGTLVT 668 28 VSSGQPK NLWGPGTLVTV 669 26 SSGQPK SQNLWGPGTLV 670 21 TVSSGQPK GGPIHYSNLWGP 671 20 GTLVTVSSGQPK GDLWGPGTLVT 672 17 VSSGQPK GMDLWGPGTLV 673 16 TVSSGQPK FFNLWGPGTLV 674 12 TVSSGQPK WGPGTLVTVSS 675 10 GQPK SFNLWGPGTLVT 676 10 VSSGQPK FDLWGPGTLVT 677 10 VSSGQPK HFNLWGPGTLV 678 9 TVSSGQPK DYFLWGPGTLV 679 9 TVSSGQPK DWGLWGPGTLV 680 9 TVSSGQPK GVGLWGPGTLV 681 8 TVSSGQPK GFFNLWGPGTL 682 7 VTVSSGQPK SSLLWGPGTLVT 683 7 VSSGQPK YLWGPGTLVTV 684 6 SSGQPK YFSLWGPGTLVT 685 6 VSSGQPK YAPFNLWGPGT 686 5 LVTVSSGQPK FNFWGPGTLVT 687 5 VSSGQPK SYILWGPGTLVT 688 4 VSSGQPK GFNLWGPGTLV 689 3 TVSSGQPK FDFWGPGTLVT 690 3 VSSGQPK DLGLWGPGTLV 691 3 TVSSGQPK LWGPGTVVTVSS 692 3 GQPK LWGPGTLVTVS 693 3 AGQPK YFTLWGPGTLV 694 3 TVSSGQPK DLWGPGTLVTV 695 2 SSGQPK LFNLWGPGTLV 696 2 TVSSGQPK ECGLWGPGTLV 697 2 TVSSGQPK DYDLWGPGTLV 698 2 TVSSGQPK ADGGTYNLWGP 699 2 GTLVTVSSGQPK AFNLWGPGTLV 700 2 TVSSGQPK VFNLWGPGTLV 701 2 TVSSGQPK TGYIGDGYPFNL 702 2 WGPGTLVTVSS GQPK EGIYFDLWGPGT 703 2 LVTVSSGQPK SYGASDLWGPG 704 2 TLVTVSSGQPK YAFDPWGPGTL 705 2 VTVSSGQPK NYNLWGPGTLV 706 2 TVSSGQPK NFGLWGPGTLV 707 1 TVSSGQPK DLWGQGTLVTV 708 1 SSGQPK DSGYLWGPGTL 709 1 VTVSSGQPK DGSVDYDLWGP 710 1 GTLVTVSSGQPK SADGSSASGMHL 711 1 WGPGTLVTVSS GQPK NICPSTDINLWG 712 1 PGTLVTVSSGQP K SYAPTLWGPGTL 713 1 VTVSSGQPK QYLLWGPGTLV 714 1 TVSSGQPK DFNLWGPGTLV 715 1 TVSSGQPK YFMDLWGPGTL 716 1 VTVSSGQPK NGGLWGPGTLV 717 1 TVSSGQPK

All of the methods disclosed and claimed herein can be made and executed without undue experimentation in light of the present disclosure. While the compositions and methods of this invention have been described in terms of preferred embodiments, it will be apparent to those of skill in the art that variations may be applied to the methods and in the steps or in the sequence of steps of the method described herein without departing from the concept, spirit and scope of the invention. More specifically, it will be apparent that certain agents which are both chemically and physiologically related may be substituted for the agents described herein while the same or similar results would be achieved. All such similar substitutes and modifications apparent to those skilled in the art are deemed to be within the spirit, scope and concept of the invention as defined by the appended claims.

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The following references, to the extent that they provide exemplary procedural or other details supplementary to those set forth herein, are specifically incorporated herein by reference.

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What is claimed is:
 1. A method for preparing a report of the sequence information for plurality of antigen-specific antibodies comprising: (i) inputting protein mass spectra data obtained from a sample of a subject, having been exposed an antigen, into a computer; (ii) inputting nucleic acid sequence data, obtained from the sample of the subject, into the computer; (iii) running an alignment program to correlate the protein mass spectra data and the nucleic sequence data, thereby obtaining the polypeptide sequences for a plurality of antigen-specific antibodies expressed in the serum of the subject; and (iv) preparing a report of the obtained the polypeptide sequences for a plurality of antigen-specific antibodies.
 2. The method of claim 1, wherein the alignment program performs a clustering analysis.
 3. The method of claim 1, wherein the alignment program compares multiple sequences by log expectation.
 4. The method of claim 1, wherein the alignment program further provides the abundancy level of a plurality of antibodies.
 5. The method of claim 1, wherein the sample is a serum sample.
 6. The method of claim 1, wherein the sample is from a lymphoid organ.
 7. The method of claim 1, wherein the wherein the protein mass spectra data is obtained by high performance liquid chromatography (HPLC)-mass spectroscopy.
 8. The method of claim 1, wherein the wherein the protein mass spectra data is obtained from a sample that has been enriched for antibodies that bind to a predetermined antigen.
 9. The method of claim 1, wherein the wherein the protein mass spectra data is obtained from a sample that has been enriched for CDR3-containing fragments of antibodies.
 10. The method of claim 1, wherein the nucleic acid sequence data is obtained by high throughput DNA sequencing.
 11. The method of claim 10, wherein the high-throughput sequencing comprises sequencing-by-synthesis, sequencing-by-ligation, sequencing-by-hybridization, single molecule DNA sequencing, multiplex polony sequencing, nanopore sequencing, or a combination thereof.
 12. The method of claim 1, wherein the subject has a tumor, an infectious disease, an autoimmune disease or has been immunized.
 13. The method of claim 1, further comprising producing one or more of the plurality of antibodies.
 14. The method of claim 1, further comprising evaluating the binding affinity of one or more of the plurality of antibodies.
 15. The method of claim 1, wherein the plurality antigen-specific antibodies bind to an infectious agent, a tumor antigen, a tumor cell or a self-antigen.
 16. The method of claim 1, wherein the subject is a human subject.
 17. The method of claim 1, wherein the plurality antigen-specific antibodies comprise IgG, IgM, or IgA antibodies.
 18. The method of claim 1, wherein the plurality antigen-specific antibodies are IgG antibodies. 